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Probabilistic reasoning is an essential tool for robust decision-making systems because of its ability to explicitly handle real-world uncertainty, constraints and causal relations. Consequently, researchers are developing hybrid models by…

Hardware Architecture · Computer Science 2021-03-02 Nimish Shah , Laura I. Galindez Olascoaga , Wannes Meert , Marian Verhelst

Devices based on arrays of interconnected magnetic nano-rings with emergent magnetization dynamics have recently been proposed for use in reservoir computing applications, but for them to be computationally useful it must be possible to…

We construct a probabilistic quantum cloning machine by a general unitary-reduction operation. With a postselection of the measurement results, the machine yields faithful copies of the input states. It is shown that the states secretly…

Quantum Physics · Physics 2009-10-31 Lu-Ming Duan , Guang-Can Guo

In some misspecified settings, the posterior distribution in Bayesian statistics may lead to inconsistent estimates. To fix this issue, it has been suggested to replace the likelihood by a pseudo-likelihood, that is the exponential of a…

Statistics Theory · Mathematics 2019-12-12 Badr-Eddine Chérief-Abdellatif , Pierre Alquier

An algorithm is proposed for constructing quasi-random "peaked" quantum circuits, i.e., circuits whose final qubit state exhibits a high probability concentration on a specific computational basis state. These circuits consist of random…

Quantum Physics · Physics 2025-08-12 O. G. Udalov

Recent research has demonstrated that quantum computers can solve certain types of problems substantially faster than the known classical algorithms. These problems include factoring integers and certain physics simulations. Practical…

Quantum Physics · Physics 2009-10-30 Emanuel Knill , Raymond Laflamme , Wojciech H. Zurek

Inspired by the developments in quantum computing, building domain-specific classical hardware to solve computationally hard problems has received increasing attention. Here, by introducing systematic sparsification techniques, we…

Many emerging alternative models of computation require massive numbers of random bits, but their generation at low energy is currently a challenge. The superparamagnetic tunnel junction, a spintronic device based on the same technology as…

Future extreme-scale computer systems may expose silent data corruption (SDC) to applications, in order to save energy or increase performance. However, resilience research struggles to come up with useful abstract programming models for…

Mathematical Software · Computer Science 2014-01-15 James Elliott , Mark Hoemmen , Frank Mueller

Benjamini, Kalai and Schramm (2001) showed that weighted majority functions of $n$ independent unbiased bits are uniformly stable under noise: when each bit is flipped with probability $\epsilon$, the probability $p_\epsilon$ that the…

Probability · Mathematics 2007-05-23 Yuval Peres

In this paper, we develop efficient randomized algorithms for estimating probabilistic robustness margin and constructing robustness degradation curve for uncertain dynamic systems. One remarkable feature of these algorithms is their…

Optimization and Control · Mathematics 2008-05-13 Xinjia Chen , Kemin Zhou , Jorge L. Aravena

The Lipschitz constant plays a crucial role in certifying the robustness of neural networks to input perturbations. Since calculating the exact Lipschitz constant is NP-hard, efforts have been made to obtain tight upper bounds on the…

Machine Learning · Computer Science 2024-10-30 Yuezhu Xu , S. Sivaranjani

Reservoir computing has been considered as a promising intelligent computing paradigm for effectively processing complex temporal information. Exploiting tunable and reproducible dynamics in the single electronic device have been desired to…

Mesoscale and Nanoscale Physics · Physics 2023-10-19 Pengfei Wang , Moyu Chen , Yongqin Xie , Chen Pan , Kenji Watanabe , Takashi Taniguchi , Bin Cheng , Shi-Jun Liang , Feng Miao

Assessment of practical quantum information processing (QIP) remains partial without understanding limits imposed by noise. Unfortunately, mere description of noise grows exponentially with system size, becoming cumbersome even for modest…

Quantum Physics · Physics 2024-08-14 Vikesh Siddhu , John Smolin

Brains perform decision-making by Bayes theorem. The theorem quantifies events as probabilities and, based on probability rules, renders the decisions. Learning from this, Bayes theorem can be applied to enable efficient user-scene…

Machine Learning · Computer Science 2025-09-03 Lekai Song , Pengyu Liu , Yang Liu , Jingfang Pei , Wenyu Cui , Songwei Liu , Yingyi Wen , Teng Ma , Kong-Pang Pun , Leonard W. T. Ng , Guohua Hu

Mid-circuit measurements and measurement-controlled gates are supported by an increasing number of quantum hardware platforms and will become more relevant as an essential building block for quantum error correction. However, mid-circuit…

Quantum Physics · Physics 2025-02-27 Yanbin Chen , Innocenzo Fulginiti , Christian B. Mendl

As the limits of traditional von Neumann computing come into view, the brain's ability to communicate vast quantities of information using low-power spikes has become an increasing source of inspiration for alternative architectures. Key to…

Neurons and Cognition · Quantitative Biology 2020-12-02 Emily Toomey , Ken Segall , Matteo Castellani , Marco Colangelo , Nancy Lynch , Karl K. Berggren

Numerical optimization is used to design linear-optical devices that implement a desired quantum gate with perfect fidelity, while maximizing the success rate. For the 2-qubit CS (or CNOT) gate, we provide numerical evidence that the…

Quantum Physics · Physics 2015-05-13 Dmitry B. Uskov , Lev Kaplan , A. Matthew Smith , Sean D. Huver , Jonathan P. Dowling

Since their introduction in 2004, Polynomial Modular Number Systems (PMNS) have become a very interesting tool for implementing cryptosystems relying on modular arithmetic in a secure and efficient way. However, while their implementation…

Data Structures and Algorithms · Computer Science 2024-06-07 Jean Claude Bajard , Jérémy Marrez , Thomas Plantard , Pascal Véron

The Brown-Resnick max-stable process has proven to be well-suited for modeling extremes of complex environmental processes, but in many applications its likelihood function is intractable and inference must be based on a composite…

Methodology · Statistics 2017-01-16 Emeric Thibaud , Juha Aalto , Daniel S. Cooley , Anthony C. Davison , Juha Heikkinen