Close Menu
  • Home
  • AI Models
    • DeepSeek
    • xAI
    • OpenAI
    • Meta AI Llama
    • Google DeepMind
    • Amazon AWS AI
    • Microsoft AI
    • Anthropic (Claude)
    • NVIDIA AI
    • IBM WatsonX Granite 3.1
    • Adobe Sensi
    • Hugging Face
    • Alibaba Cloud (Qwen)
    • Baidu (ERNIE)
    • C3 AI
    • DataRobot
    • Mistral AI
    • Moonshot AI (Kimi)
    • Google Gemma
    • xAI
    • Stability AI
    • H20.ai
  • AI Research
    • Allen Institue for AI
    • arXiv AI
    • Berkeley AI Research
    • CMU AI
    • Google Research
    • Microsoft Research
    • Meta AI Research
    • OpenAI Research
    • Stanford HAI
    • MIT CSAIL
    • Harvard AI
  • AI Funding & Startups
    • AI Funding Database
    • CBInsights AI
    • Crunchbase AI
    • Data Robot Blog
    • TechCrunch AI
    • VentureBeat AI
    • The Information AI
    • Sifted AI
    • WIRED AI
    • Fortune AI
    • PitchBook
    • TechRepublic
    • SiliconANGLE – Big Data
    • MIT News
    • Data Robot Blog
  • Expert Insights & Videos
    • Google DeepMind
    • Lex Fridman
    • Matt Wolfe AI
    • Yannic Kilcher
    • Two Minute Papers
    • AI Explained
    • TheAIEdge
    • Matt Wolfe AI
    • The TechLead
    • Andrew Ng
    • OpenAI
  • Expert Blogs
    • François Chollet
    • Gary Marcus
    • IBM
    • Jack Clark
    • Jeremy Howard
    • Melanie Mitchell
    • Andrew Ng
    • Andrej Karpathy
    • Sebastian Ruder
    • Rachel Thomas
    • IBM
  • AI Policy & Ethics
    • ACLU AI
    • AI Now Institute
    • Center for AI Safety
    • EFF AI
    • European Commission AI
    • Partnership on AI
    • Stanford HAI Policy
    • Mozilla Foundation AI
    • Future of Life Institute
    • Center for AI Safety
    • World Economic Forum AI
  • AI Tools & Product Releases
    • AI Assistants
    • AI for Recruitment
    • AI Search
    • Coding Assistants
    • Customer Service AI
    • Image Generation
    • Video Generation
    • Writing Tools
    • AI for Recruitment
    • Voice/Audio Generation
  • Industry Applications
    • Finance AI
    • Healthcare AI
    • Legal AI
    • Manufacturing AI
    • Media & Entertainment
    • Transportation AI
    • Education AI
    • Retail AI
    • Agriculture AI
    • Energy AI
  • AI Art & Entertainment
    • AI Art News Blog
    • Artvy Blog » AI Art Blog
    • Weird Wonderful AI Art Blog
    • The Chainsaw » AI Art
    • Artvy Blog » AI Art Blog
What's Hot

AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning – Takara TLDR

China reportedly discouraged purchase of NVIDIA AI chips due to ‘insulting’ Lutnick statements

Tool-space interference in the MCP era: Designing for agent compatibility at scale

Facebook X (Twitter) Instagram
Advanced AI News
  • Home
  • AI Models
    • OpenAI (GPT-4 / GPT-4o)
    • Anthropic (Claude 3)
    • Google DeepMind (Gemini)
    • Meta (LLaMA)
    • Cohere (Command R)
    • Amazon (Titan)
    • IBM (Watsonx)
    • Inflection AI (Pi)
  • AI Research
    • Allen Institue for AI
    • arXiv AI
    • Berkeley AI Research
    • CMU AI
    • Google Research
    • Meta AI Research
    • Microsoft Research
    • OpenAI Research
    • Stanford HAI
    • MIT CSAIL
    • Harvard AI
  • AI Funding
    • AI Funding Database
    • CBInsights AI
    • Crunchbase AI
    • Data Robot Blog
    • TechCrunch AI
    • VentureBeat AI
    • The Information AI
    • Sifted AI
    • WIRED AI
    • Fortune AI
    • PitchBook
    • TechRepublic
    • SiliconANGLE – Big Data
    • MIT News
    • Data Robot Blog
  • AI Experts
    • Google DeepMind
    • Lex Fridman
    • Meta AI Llama
    • Yannic Kilcher
    • Two Minute Papers
    • AI Explained
    • TheAIEdge
    • The TechLead
    • Matt Wolfe AI
    • Andrew Ng
    • OpenAI
    • Expert Blogs
      • François Chollet
      • Gary Marcus
      • IBM
      • Jack Clark
      • Jeremy Howard
      • Melanie Mitchell
      • Andrew Ng
      • Andrej Karpathy
      • Sebastian Ruder
      • Rachel Thomas
      • IBM
  • AI Tools
    • AI Assistants
    • AI for Recruitment
    • AI Search
    • Coding Assistants
    • Customer Service AI
  • AI Policy
    • ACLU AI
    • AI Now Institute
    • Center for AI Safety
  • Business AI
    • Advanced AI News Features
    • Finance AI
    • Healthcare AI
    • Education AI
    • Energy AI
    • Legal AI
LinkedIn Instagram YouTube Threads X (Twitter)
Advanced AI News
IBM

Lockheed uses IBM quantum processor to solve major chemistry puzzle

By Advanced AI EditorMay 23, 2025No Comments3 Mins Read
Share Facebook Twitter Pinterest Copy Link Telegram LinkedIn Tumblr Email
Share
Facebook Twitter LinkedIn Pinterest Email


Researchers at IBM and Lockheed Martin teamed up high-performance computing with quantum computing to accurately model the electronic structure of ‘open-shell’ molecules, methylene, which has been a hurdle with classic computing over the years. This is the first demonstration of the sample-based quantum diagonalization (SQD) technique to open-shell systems, a press release said. 

Quantum computing, which promises computations at speeds unimaginable by even the fastest supercomputers of today, is the next frontier of computing. Leveraging quantum states of molecules to serve as quantum bits, these computers supersede computational capabilities that humanity has had access to in the past and open up new research areas.

Quantum chemistry is one such area of interest where understanding the interaction between molecules can help design more efficient processes for industrial applications as well as material research. However, chemical systems involving strong electron correlation have been exceptionally hard to simulate, even on high-performance computing platforms. 

The challenge with open-shell systems

Classical approximation methods used for simulating chemical systems with strong electronic correlation exist. However, computational costs associated with systems increase exponentially with the number of electrons involved. 

Understanding energy states and how molecules transition from one state to another is crucial to our understanding of chemistry. Doing so allows scientists to predict their reactivity and how they will interact with catalysts or leverage their excited state to carry out sensing or aerospace applications and much more.  

The challenge of these simulations is even higher with ‘open-shell systems’ where molecules contain one or more unpaired electrons. Unlike their closed-shell counterparts, whose electrons are paired in orbitals and have simple and stable wave functions, open-shell molecules are highly reactive, can exhibit magnetic properties, and need multiple wave functions to capture their complexity. 

Researchers at IBM and Lockheed Martin were especially interested in understanding the reactivity of methylene, one such open-shell molecule, and examined it using a combination of high-performance and quantum computing. 

Difference between energy states of methylene molecules.
Difference between energy states of methylene molecules. Image credit: IBM

Why did the team study methylene? 

Methylene (CH2) is composed of three atoms but is quite complex in nature. In its ground state, the molecule adopts a triplet electronic structure where the carbon atom’s outer shell consists of two unpaired electrons with parallel spins. This is a highly energetic state, and the molecule is not generally found in it. 

The molecule has a first excited state called carbene singlet state where two electrons in the carbon atom are paired with opposite spins and one orbital is empty. In its triplet state, the two electrons are unpaired with spins in the same direction. This leads to a rare occurrence where the molecule’s triplet state is lower than its singlet state. 

The energy difference between the singlet-triplet states is crucial since it allows scientists to predict how the molecule will interact in a chemical reaction. Using IBM’s quantum-centric supercomputing framework, combining high-performance computing with quantum processors, the researchers applied the Sample-based Quantum Diagonalization (SQD) method and computed methylene’s singlet and triplet states, their dissociation energies and energy gaps. 

Molecules such as methylene are crucial for aerospace and combustion chemistry and help design better engines, while also helping demonstrate the present-day application of quantum computing. 



Source link

Follow on Google News Follow on Flipboard
Share. Facebook Twitter Pinterest LinkedIn Tumblr Email Copy Link
Previous ArticleExclusive: AI Bests Virus Experts, Raising Biohazard Fears
Next Article Fast Isn’t Enough — Fix It Right
Advanced AI Editor
  • Website

Related Posts

Amazon, IBM, and Dell helped build China’s surveillance state brick by brick, investigation finds

September 9, 2025

IBM vs. QCOM: Which Tech Stock Deserves a Spot in Your Portfolio Now? – September 9, 2025

September 9, 2025

IBM Declines 8.6% in 3 Months: Should You Rethink the Stock? – September 8, 2025

September 8, 2025
Leave A Reply

Latest Posts

National Gallery and Tate Have ‘Bad Blood’—and More Art News

Christie’s Will Auction The First Calculating Machine In History

The Art Market Isn’t Dying. The Way We Write About It Might Be.

Banksy Mural of Judge Beating Protestor Removed by Courts Service

Latest Posts

AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning – Takara TLDR

September 11, 2025

China reportedly discouraged purchase of NVIDIA AI chips due to ‘insulting’ Lutnick statements

September 11, 2025

Tool-space interference in the MCP era: Designing for agent compatibility at scale

September 11, 2025

Subscribe to News

Subscribe to our newsletter and never miss our latest news

Subscribe my Newsletter for New Posts & tips Let's stay updated!

Recent Posts

  • AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning – Takara TLDR
  • China reportedly discouraged purchase of NVIDIA AI chips due to ‘insulting’ Lutnick statements
  • Tool-space interference in the MCP era: Designing for agent compatibility at scale
  • Peak bubble – by Gary Marcus
  • Hunyuan-MT Technical Report – Takara TLDR

Recent Comments

  1. RobertVew on 1-800-CHAT-GPT—12 Days of OpenAI: Day 10
  2. loads on 1-800-CHAT-GPT—12 Days of OpenAI: Day 10
  3. MichaelSmica on 1-800-CHAT-GPT—12 Days of OpenAI: Day 10
  4. GilbertDix on 1-800-CHAT-GPT—12 Days of OpenAI: Day 10
  5. RichardBub on 1-800-CHAT-GPT—12 Days of OpenAI: Day 10

Welcome to Advanced AI News—your ultimate destination for the latest advancements, insights, and breakthroughs in artificial intelligence.

At Advanced AI News, we are passionate about keeping you informed on the cutting edge of AI technology, from groundbreaking research to emerging startups, expert insights, and real-world applications. Our mission is to deliver high-quality, up-to-date, and insightful content that empowers AI enthusiasts, professionals, and businesses to stay ahead in this fast-evolving field.

Subscribe to Updates

Subscribe to our newsletter and never miss our latest news

Subscribe my Newsletter for New Posts & tips Let's stay updated!

LinkedIn Instagram YouTube Threads X (Twitter)
  • Home
  • About Us
  • Advertise With Us
  • Contact Us
  • DMCA
  • Privacy Policy
  • Terms & Conditions
© 2025 advancedainews. Designed by advancedainews.

Type above and press Enter to search. Press Esc to cancel.