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Related Concept Videos

Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...

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Related Experiment Video

Updated: May 17, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

Sub-mV tunable photonic p-bits for probabilistic computing.

Juhyung Seo1, Taehyun Park1, Jun-Young Park2

  • 1Department of Electronic Engineering, Hanyang University, Seoul 04763, Republic of Korea.

Science Advances
|May 15, 2026
PubMed
Summary
This summary is machine-generated.

New light-controlled probabilistic bits (p-bits) enable tunable randomness for solving complex computational problems. This breakthrough paves the way for scalable probabilistic computing (p-computing) and energy-based optimization.

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A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
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A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

Related Experiment Videos

Last Updated: May 17, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
07:56

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

Area of Science:

  • Quantum Computing and Information Science
  • Materials Science and Engineering
  • Computational Science

Background:

  • Randomness is increasingly recognized as a valuable resource for intelligent computation, moving beyond its traditional role as noise.
  • Probabilistic bits (p-bits) offer a novel approach to computation by utilizing stochastic logic and energy-based optimization for complex problem-solving.
  • Existing p-bit technologies face challenges in stable control of output probability, hindering scalability for probabilistic computing (p-computing).

Purpose of the Study:

  • To introduce and characterize novel light-induced bias-tunable probabilistic-bit (LBP-bit) devices.
  • To demonstrate a new framework for scalable probabilistic computing (p-computing) using LBP-bits.
  • To showcase the application of LBP-bits in solving computationally intensive problems like integer factorization and Max-Cut.

Main Methods:

  • Development of LBP-bit devices based on light-induced charge polarity switching in a back-to-back junction.
  • Precise tuning of the stochastic bitstream probability using submillivolt bias, independent of the randomness generation mechanism.
  • Implementation of a p-computing framework to evaluate performance on integer factorization and Max-Cut problems.

Main Results:

  • LBP-bits successfully generate entropy through light-induced switching, providing a tunable source of randomness.
  • The probability of the stochastic output is precisely controlled with minimal bias, demonstrating stable probability control.
  • The proposed p-computing framework effectively solves representative problems in integer factorization and combinatorial optimization (Max-Cut).

Conclusions:

  • The unique separation of randomness generation (light) and probability control (bias) in LBP-bits is crucial for scalable p-computing.
  • Light serves as an effective stochastic source in these devices, enabling probabilistic computation for complex tasks.
  • LBP-bits represent a significant advancement towards practical and scalable probabilistic computing architectures.