scispace - formally typeset
Search or ask a question
Institution

IBM

CompanyArmonk, New York, United States
About: IBM is a company organization based out in Armonk, New York, United States. It is known for research contribution in the topics: Layer (electronics) & Cache. The organization has 134567 authors who have published 253905 publications receiving 7458795 citations. The organization is also known as: International Business Machines Corporation & Big Blue.


Papers
More filters
Journal ArticleDOI
TL;DR: In this article, it was shown that the paraelectric phase stabilizes below 4 K with a very high dielectric constant and the crossover from classical to quantum behavior on lowering the temperature is discussed, and the coupling of the ferroelectric mode to acoustic ones is important.
Abstract: The dielectric constants ${\ensuremath{\epsilon}}_{〈110〉}$ and their change with uniaxial $〈1\overline{1}0〉$ stress in monodomain $〈001〉$SrTi${\mathrm{O}}_{3}$ samples have been measured as a function of temperature. Between 4 K and 0.3 K these quantities are independent of temperature. In one sample $\ensuremath{\epsilon}(T)$ was measured to 0.035 K and found to be constant. This proves the quantum-mechanical stabilization of the paraelectric phase below 4 K with a very high dielectric constant $\ensuremath{\epsilon}$. The crossover from classical to quantum behavior on lowering the temperature is discussed, and it is shown that the coupling of the ferroelectric mode to acoustic ones is important. The $\ensuremath{\epsilon}(T)$ dependence is compared to earlier and recent theories. The former, yielding a coth ($\frac{\ensuremath{\hbar}\ensuremath{\Omega}}{\mathrm{kT}}$) term, are found to be inadequate for the crossover region. A recent biquadratic ferroelectric mode-coupling theory fits the data better.

1,429 citations

Journal ArticleDOI
20 Dec 2001-Nature
TL;DR: A simple, parameter-free but predictive model of decoherence effects in the authors' system is presented, which is in principle scalable to systems containing many quantum bits, but such scalability is not implied by the present work.
Abstract: The number of steps any classical computer requires in order to find the prime factors of an l-digit integer N increases exponentially with l, at least using algorithms known at present. Factoring large integers is therefore conjectured to be intractable classically, an observation underlying the security of widely used cryptographic codes. Quantum computers, however, could factor integers in only polynomial time, using Shor's quantum factoring algorithm. Although important for the study of quantum computers, experimental demonstration of this algorithm has proved elusive. Here we report an implementation of the simplest instance of Shor's algorithm: factorization of N = 15 (whose prime factors are 3 and 5). We use seven spin-1/2 nuclei in a molecule as quantum bits, which can be manipulated with room temperature liquid-state nuclear magnetic resonance techniques. This method of using nuclei to store quantum information is in principle scalable to systems containing many quantum bits, but such scalability is not implied by the present work. The significance of our work lies in the demonstration of experimental and theoretical techniques for precise control and modelling of complex quantum computers. In particular, we present a simple, parameter-free but predictive model of decoherence effects in our system.

1,429 citations

Journal ArticleDOI
TL;DR: In this paper, the authors performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data.
Abstract: Reconstructing gene regulatory networks from high-throughput data is a long-standing challenge. Through the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data. We characterize the performance, data requirements and inherent biases of different inference approaches, and we provide guidelines for algorithm application and development. We observed that no single inference method performs optimally across all data sets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse data sets. We thereby constructed high-confidence networks for E. coli and S. aureus, each comprising ~1,700 transcriptional interactions at a precision of ~50%. We experimentally tested 53 previously unobserved regulatory interactions in E. coli, of which 23 (43%) were supported. Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks.

1,424 citations

Journal ArticleDOI
TL;DR: In this article, the authors deal with selected topics regarding the properties of simple condensed matter systems, especially metals, and find that considerable experimental and conceptual progress has been made, but specific physical processes mostly remain to be identified.
Abstract: An astonishing variety of systems show properties that fluctuate with approximately $\frac{1}{f}$-shaped spectral densities. In this review we deal with selected topics regarding $\frac{1}{f}$ fluctuations (or noise) in the resistance of simple condensed matter systems, especially metals. We find that considerable experimental and conceptual progress has been made, but specific physical processes mostly remain to be identified.

1,419 citations

Proceedings ArticleDOI
04 Apr 2018
TL;DR: The most recent edition of the dermoscopic image analysis benchmark challenge as discussed by the authors was organized to support research and development of algorithms for automated diagnosis of melanoma, the most lethal skin cancer.
Abstract: This article describes the design, implementation, and results of the latest installment of the dermoscopic image analysis benchmark challenge. The goal is to support research and development of algorithms for automated diagnosis of melanoma, the most lethal skin cancer. The challenge was divided into 3 tasks: lesion segmentation, feature detection, and disease classification. Participation involved 593 registrations, 81 pre-submissions, 46 finalized submissions (including a 4-page manuscript), and approximately 50 attendees, making this the largest standardized and comparative study in this field to date. While the official challenge duration and ranking of participants has concluded, the dataset snapshots remain available for further research and development.

1,419 citations


Authors

Showing all 134658 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Anil K. Jain1831016192151
Hyun-Chul Kim1764076183227
Rodney S. Ruoff164666194902
Tobin J. Marks1591621111604
Jean M. J. Fréchet15472690295
Albert-László Barabási152438200119
György Buzsáki15044696433
Stanislas Dehaene14945686539
Philip S. Yu1481914107374
James M. Tour14385991364
Thomas P. Russell141101280055
Naomi J. Halas14043582040
Steven G. Louie13777788794
Daphne Koller13536771073
Network Information
Related Institutions (5)
Carnegie Mellon University
104.3K papers, 5.9M citations

93% related

Georgia Institute of Technology
119K papers, 4.6M citations

92% related

Bell Labs
59.8K papers, 3.1M citations

90% related

Microsoft
86.9K papers, 4.1M citations

89% related

Massachusetts Institute of Technology
268K papers, 18.2M citations

88% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202330
2022137
20213,163
20206,336
20196,427
20186,278