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With the current rate of progress in quantum computing technologies, systems with more than 50 qubits will soon become reality. Computing ideal quantum state amplitudes for circuits of such and larger sizes is a fundamental step to assess…

Over-the-Air Computation (OAC) enables efficient data aggregation in large-scale distributed systems by exploiting the superposition property of wireless multiple-access channels. In contrast to most existing studies on OAC assuming exact…

Signal Processing · Electrical Eng. & Systems 2026-05-28 Martin Dahl , Zheng Chen , Erik G. Larsson

Intermediate reasoning or acting steps have successfully improved large language models (LLMs) for handling various downstream natural language processing (NLP) tasks. When applying LLMs for code generation, recent works mainly focus on…

Computation and Language · Computer Science 2024-06-25 Tao Sun , Linzheng Chai , Jian Yang , Yuwei Yin , Hongcheng Guo , Jiaheng Liu , Bing Wang , Liqun Yang , Zhoujun Li

The challenge of quantum computing is to combine error resilience with universal computation. Diagonal gates such as the transversal $T$ gate play an important role in implementing a universal set of quantum operations. This paper…

Quantum Physics · Physics 2022-09-14 Jingzhen Hu , Qingzhong Liang , Robert Calderbank

For nonnegative integers $n,d,w$, let $A(n,d,w)$ be the maximum size of a code $C \subseteq \mathbb{F}_2^n$ with constant weight $w$ and minimum distance at least $d$. We consider two semidefinite programs based on quadruples of code words…

Combinatorics · Mathematics 2019-06-12 Sven Polak

The standard method of generating random weights and biases in feedforward neural networks with random hidden nodes, selects them both from the uniform distribution over the same fixed interval. In this work, we show the drawbacks of this…

Machine Learning · Computer Science 2019-09-18 Grzegorz Dudek

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is…

Information Theory · Computer Science 2007-07-13 Pierre Moulin , Ying Wang

We determine the optimal rates of universal quantum codes for entanglement transmission and generation under channel uncertainty. In the simplest scenario the sender and receiver are provided merely with the information that the channel…

Quantum Physics · Physics 2015-05-13 I. Bjelakovic , H. Boche , J. Noetzel

In this paper we consider the variable-length lossless source coding for discrete memoryless sources. We proposes a new encryption framework for securely transmitting codewords over a noiseless channel. The proposed source encryption…

Information Theory · Computer Science 2026-05-26 Yasutada Oohama , Bagus Santoso

We introduce the notion of distributed quantum dense coding, i.e. the generalization of quantum dense coding to more than one sender and more than one receiver. We show that global operations (as compared to local operations) of the senders…

A technique of lossless compression via substring enumeration (CSE) attains compression ratios as well as popular lossless compressors for one-dimensional (1D) sources. The CSE utilizes a probabilistic model built from the circular string…

Information Theory · Computer Science 2017-01-25 Takahiro Ota , Hiroyoshi Morita

This article introduces an algorithm to draw random discrete uniform variables within a given range of size n from a source of random bits. The algorithm aims to be simple to implement and optimal both with regards to the amount of random…

Data Structures and Algorithms · Computer Science 2013-04-09 Jérémie Lumbroso

In this study we consider rateless coding over discrete memoryless channels (DMC) with feedback. Unlike traditional fixed-rate codes, in rateless codes each codeword is infinitely long, and the decoding time depends on the confidence level…

Information Theory · Computer Science 2012-01-30 Navot Blits

We propose a principled method for autoencoding with random forests. Our strategy builds on foundational results from nonparametric statistics and spectral graph theory to learn a low-dimensional embedding of the model that optimally…

Machine Learning · Statistics 2026-01-16 Binh Duc Vu , Jan Kapar , Marvin Wright , David S. Watson

In this paper, we investigate the redundancy of universal coding schemes on smooth parametric sources in the finite-length regime. We derive an upper bound on the probability of the event that a sequence of length $n$, chosen using…

Information Theory · Computer Science 2011-10-27 Ahmad Beirami , Faramarz Fekri

Consider the following framework of universal decoding suggested in [MerhavUniversal]. Given a family of decoding metrics and random coding distribution (prior), a single, universal, decoder is optimal if for any possible channel the…

Information Theory · Computer Science 2014-04-29 Nir Elkayam , Meir Feder

The problem of lossless fixed-rate streaming coding of discrete memoryless sources with side information at the decoder is studied. A random time-varying tree-code is used to sequentially bin strings and a Stack Algorithm with a variable…

Information Theory · Computer Science 2007-07-13 Hari Palaiyanur , Anant Sahai

We describe a general method for turning quantum circuits into sparse quantum subsystem codes. The idea is to turn each circuit element into a set of low-weight gauge generators that enforce the input-output relations of that circuit…

Quantum Physics · Physics 2017-03-28 Dave Bacon , Steven T. Flammia , Aram W. Harrow , Jonathan Shi

Transformers have impressive generalization capabilities on tasks with a fixed context length. However, they fail to generalize to sequences of arbitrary length, even for seemingly simple tasks such as duplicating a string. Moreover, simply…

This paper revisits the ordered statistics decoding (OSD). It provides a comprehensive analysis of the OSD algorithm by characterizing the statistical properties, evolution and the distribution of the Hamming distance and weighted Hamming…

Information Theory · Computer Science 2021-05-10 Chentao Yue , Mahyar Shirvanimoghaddam , Branka Vucetic , Yonghui Li
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