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Related papers: Optimal finite-time bit erasure under full control

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We study the capacity region of the two-user Binary Fading (or Erasure) Interference Channel where the transmitters have no knowledge of the channel state information. We develop new inner-bounds and outer-bounds for this problem. We…

Information Theory · Computer Science 2017-03-28 Alireza Vahid , Mohammad Ali Maddah-Ali , Amir Salman Avestimehr , Yan Zhu

We demonstrate an information erasure protocol that resets $N$ qubits at once. The method displays exceptional performances in terms of energy cost (it operates nearly at Landauer energy cost $kT \ln 2$), time duration ($\sim \mu s$) and…

Quantum Physics · Physics 2023-03-29 Lorenzo Buffoni , Michele Campisi

In this paper, we present an advanced analysis of near optimal algorithms that use limited space to solve the frequency estimation, heavy hitters, frequent items, and top-k approximation in the bounded deletion model. We define the family…

Exact free energy minimization is a convex optimization problem that is usually approximated with stochastic sampling methods. Deterministic approximations have been less successful because many desirable properties have been difficult to…

Computational Physics · Physics 2016-03-17 Jonathan E. Moussa

We introduce an algorithm where the individual bits representing the weights of a neural network are learned. This method allows training weights with integer values on arbitrary bit-depths and naturally uncovers sparse networks, without…

Machine Learning · Computer Science 2022-02-22 Cristian Ivan

Landauer's principle makes a strong connection between information theory and thermodynamics by stating that erasing a one-bit memory at temperature $T_0$ requires an average energy larger than $W_{LB}=k_BT_0 \ln2$, with $k_B$ Boltzmann's…

Statistical Mechanics · Physics 2024-01-12 Salambô Dago , Sergio Ciliberto , Ludovic Bellon

We study the minimization of the expected costs under stochastic constraint at the terminal time. The first and the main result says that for a power type of costs, the value function is the minimal positive solution of a second order…

Probability · Mathematics 2020-01-28 Yan Dolinsky , Benjamin Gottesman , Ori Gurel-Gurevich

The aim of power management policies is to reduce the amount of energy consumed by computer systems while maintaining satisfactory level of performance. One common method for saving energy is to simply suspend the system during the idle…

Data Structures and Algorithms · Computer Science 2010-09-06 Philippe Baptiste , Marek Chrobak , Christoph Durr

We construct constant-sized ensembles of linear error-correcting codes over any fixed alphabet that can correct a given fraction of adversarial erasures at rates approaching the Singleton bound arbitrarily closely. We provide several…

Information Theory · Computer Science 2025-04-07 Yeyuan Chen , Mahdi Cheraghchi , Nikhil Shagrithaya

This work proves new results on the ability of binary Reed-Muller codes to decode from random errors and erasures. We obtain these results by proving improved bounds on the weight distribution of Reed-Muller codes of high degrees.…

Information Theory · Computer Science 2018-12-03 Ori Sberlo , Amir Shpilka

We develop an energy-decreasing algorithm for the finite element approximation of two-dimensional ferronematic equilibrium states. The problem is formulated as the minimization of the harmonic energy of two two-dimensional vector fields,…

Numerical Analysis · Mathematics 2026-05-13 Alexandre Ern , Ruma R. Maity

Losses in quantum communication lines severely affect the rates of reliable information transmission and are usually considered to be state-independent. However, the loss probability does depend on the system state in general, with the…

Quantum Physics · Physics 2021-06-01 Sergey N. Filippov

Flash memory is a non-volatile computer memory comprised of blocks of cells, wherein each cell can take on q different levels corresponding to the number of electrons it contains. Increasing the cell level is easy; however, reducing a cell…

Information Theory · Computer Science 2015-03-13 Eitan Yaakobi , Alexander Vardy , Paul H. Siegel , Jack K. Wolf

We propose a novel approach to reduce memory consumption of the backpropagation through time (BPTT) algorithm when training recurrent neural networks (RNNs). Our approach uses dynamic programming to balance a trade-off between caching of…

Neural and Evolutionary Computing · Computer Science 2016-06-13 Audrūnas Gruslys , Remi Munos , Ivo Danihelka , Marc Lanctot , Alex Graves

We study first-order optimization algorithms under the constraint that the descent direction is quantized using a pre-specified budget of $R$-bits per dimension, where $R \in (0 ,\infty)$. We propose computationally efficient optimization…

Machine Learning · Computer Science 2022-08-17 Rajarshi Saha , Mert Pilanci , Andrea J. Goldsmith

Continuous-time stochastic processes pervade everyday experience, and the simulation of models of these processes is of great utility. Classical models of systems operating in continuous-time must typically track an unbounded amount of…

Quantum Physics · Physics 2018-03-05 Thomas J. Elliott , Mile Gu

We analyze the physics of optimal protocols to prepare a target state with high fidelity in a symmetrically coupled two-qubit system. By varying the protocol duration, we find a discontinuous phase transition, which is characterized by a…

Statistical Mechanics · Physics 2018-05-17 Marin Bukov , Alexandre G. R. Day , Phillip Weinberg , Anatoli Polkovnikov , Pankaj Mehta , Dries Sels

Dual-rail erasure qubits can substantially improve the efficiency of quantum error correction, allowing lower error rates to be achieved with fewer qubits, but each erasure qubit requires $3\times$ more transmons to implement compared to…

Quantum Physics · Physics 2025-09-04 Jason D. Chadwick , Mariesa H. Teo , Joshua Viszlai , Willers Yang , Frederic T. Chong

We introduce a new approach to proving that a sequence of deterministic linear codes achieves capacity on an erasure channel under maximum a posteriori decoding. Rather than relying on the precise structure of the codes our method exploits…

Information Theory · Computer Science 2016-01-19 Shrinivas Kudekar , Santhosh Kumar , Marco Mondelli , Henry D. Pfister , Eren Şaşoğlu , Rüdiger Urbanke

Large Language Models (LLMs) are typically trained in two phases: pre-training on large internet-scale datasets, and fine-tuning for downstream tasks. Given the higher computational demand of pre-training, it's intuitive to assume that…

Machine Learning · Computer Science 2024-10-15 James Liu , Guangxuan Xiao , Kai Li , Jason D. Lee , Song Han , Tri Dao , Tianle Cai
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