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Random quantum circuits have played a central role in establishing the computational advantages of near-term quantum computers over their conventional counterparts. Here, we use ensembles of low-depth random circuits with local connectivity…

Quantum Physics · Physics 2021-09-29 Michael J. Gullans , Stefan Krastanov , David A. Huse , Liang Jiang , Steven T. Flammia

Molecular communication is set to play an important role in the design of complex biological and chemical systems. An important class of molecular communication systems is based on the timing channel, where information is encoded in the…

Information Theory · Computer Science 2014-10-22 Malcolm Egan , Yansha Deng , Maged Elkashlan , Trung Q. Duong

We derive several efficiently computable converse bounds for quantum communication over quantum channels in both the one-shot and asymptotic regime. First, we derive one-shot semidefinite programming (SDP) converse bounds on the amount of…

Quantum Physics · Physics 2019-05-06 Xin Wang , Kun Fang , Runyao Duan

Spectrum resources management of growing demands is a challenging problem and Cognitive Radio (CR) known to be capable of improving the spectrum utilization. Recently, Power Spectral Density (PSD) map is defined to enable the CR to reuse…

Information Theory · Computer Science 2017-03-17 Mohammad Eslami , Seyed Hamid Safavi , Farah Torkamani-Azar , Esfandiar Mehrshahi

One-shot information theory addresses scenarios in source coding and channel coding where the signal blocklength is assumed to be 1. In this case, each source and channel can be used only once, and the sources and channels are arbitrary and…

Information Theory · Computer Science 2025-11-26 Yanxiao Liu

This paper studies the third-order characteristic of nonsingular discrete memoryless channels and the Gaussian channel with a maximal-power constraint. The third-order term in our expansions employs a new quantity here called the channel…

Information Theory · Computer Science 2024-08-23 Recep Can Yavas , Victoria Kostina , Michelle Effros

Compressive sensing (CS) is a signal processing technique that enables sub-Nyquist sampling and near lossless reconstruction of a sparse signal. The technique is particularly appealing for neural signal processing since it avoids the issues…

Signal Processing · Electrical Eng. & Systems 2021-02-02 Hyunseok Park , Xilin Liu

Sampled-data (SD) systems, which are composed of both discrete- and continuous-time components, are arguably one of the most common classes of cyberphysical systems in practice; most modern controllers are implemented on digital platforms…

Systems and Control · Computer Science 2014-05-13 Shahab Kaynama , Jeremy H. Gillula , Claire J. Tomlin

Reinforcement Learning (RL) controllers have generated excitement within the control community. The primary advantage of RL controllers relative to existing methods is their ability to optimize uncertain systems independently of explicit…

Machine Learning · Computer Science 2021-12-07 Max Mowbray , Panagiotis Petsagkourakis , Ehecatl Antonio del Río Chanona , Dongda Zhang

We revisit the so-called sampling and discarding approach used to quantify the probability of constraint violation of a solution to convex scenario programs when some of the original samples are allowed to be discarded. Motivated by two…

Optimization and Control · Mathematics 2022-04-05 Licio Romao , Antonis Papachristodoulou , Kostas Margellos

Training over sparse multipath channels is explored. The energy allocation and the optimal shape of training signals that enable error free communications over unknown channels are characterized as a function of the channels' statistics.…

Information Theory · Computer Science 2011-02-18 Elchanan Zwecher , Dana Porrat

Real-time end-to-end task scheduling in networked control systems (NCSs) requires the joint consideration of both network and computing resources to guarantee the desired quality of service (QoS). This paper introduces a new model for…

Networking and Internet Architecture · Computer Science 2022-10-21 Peng Wu , Chenchen Fu , Tianyu Wang , Minming Li , Yingchao Zhao , Chun Jason Xue , Song Han

A new reweighted l1-norm penalized least mean square (LMS) algorithm for sparse channel estimation is proposed and studied in this paper. Since standard LMS algorithm does not take into account the sparsity information about the channel…

Information Theory · Computer Science 2014-05-09 Omid Taheri , Sergiy A. Vorobyov

Enhanced processing power in the cloud allows constrained devices to offload costly computations: for instance, complex data analytics tasks can be computed by remote servers. Remote execution calls for a new compression paradigm that…

Information Theory · Computer Science 2021-11-18 Fabrizio Carpi , Siddharth Garg , Elza Erkip

Crossbar resistive memory with the 1 Selector 1 Resistor (1S1R) structure is attractive for nonvolatile, high-density, and low-latency storage-class memory applications. As technology scales down to the single-nm regime, the increasing…

Systems and Control · Electrical Eng. & Systems 2021-04-30 Zehui Chen , Lara Dolecek

An analog source is to be transmitted across a Gaussian channel in more than one channel use per source symbol. This paper derives a lower bound on the asymptotic mean squared error for a strategy that consists of repeatedly quantizing the…

Information Theory · Computer Science 2016-11-17 Marius Kleiner , Bixio Rimoldi

Various studies that address the compressed sensing problem with Multiple Measurement Vectors (MMVs) have been recently carried. These studies assume the vectors of the different channels to be jointly sparse. In this paper, we relax this…

Machine Learning · Computer Science 2016-11-14 Hamid Palangi , Rabab Ward , Li Deng

We investigate the classical communication over quantum channels when assisted by no-signaling (NS) and positive-partial-transpose-preserving (PPT) codes, for which both the optimal success probability of a given transmission rate and the…

Quantum Physics · Physics 2018-07-16 Xin Wang , Wei Xie , Runyao Duan

This paper examines the maximum code rate achievable by a data-driven communication system over some unknown discrete memoryless channel in the finite blocklength regime. A class of channel codes, called learning-based channel codes, is…

Information Theory · Computer Science 2023-07-18 Neil Irwin Bernardo , Jingge Zhu , Jamie Evans

Quantum channel discrimination has been studied from an information-theoretic perspective, wherein one is interested in the optimal decay rate of error probabilities as a function of the number of unknown channel accesses. In this paper, we…

Quantum Physics · Physics 2025-10-28 Theshani Nuradha , Mark M. Wilde