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IBM expands India quantum research as Japan backs quantum immunotherapy project

IBM said on 2 October it is widening two long-running research collaborations in India, with IIT Bombay and the Indian Institute of Science, covering quantum algorithm development alongside agentic and sovereign AI. The same day, a five-organisation Japanese project using quantum computing for cancer immunotherapy was picked for NEDO funding.

TechnologyAnalysisGrace OkonkwoPublished: 2 October 20263 min readSources 10
IBM expands India quantum research as Japan backs quantum immunotherapy project

IBM has expanded two research partnerships in India, the company said on 2 October, extending work with the Indian Institute of Technology Bombay that began in 2018 and with the Indian Institute of Science that began in 2021. HPCwire reported the announcement the same day. The IISc strand covers agentic systems, AI for applications and quantum computing algorithm development.

The quantum part is narrow and specific. According to HPCwire, the two sides will explore orchestration for quantum and high-performance computing, using approximation-tolerant classical diagonalization algorithms to improve quantum subspace iteration methods. No hardware, qubit count or delivery date was given.

Dr. Amith Singhee, director of IBM Research India and CTO for IBM India and South Asia, framed the work broadly: “The next wave of computing will be shaped by advances in agentic AI, sovereign AI, and quantum computing,” he said, according to the HPCwire report.

Tokyo puts quantum compute behind cancer immunotherapy

Also on 2 October, a joint Japanese project on next-generation cancer immunotherapy using quantum computing was selected for the Large-Scale Demonstration for Use Case Creation under a NEDO programme. NEC, Taiho Pharmaceutical, the Japanese Foundation for Cancer Research, AIST and Waseda University are the five participants, HPCwire reported. The goal is a computational and evaluation platform for designing and immunologically validating neoantigen candidates.

Waseda's principal investigator is Professor Nozomu Togawa of the Faculty of Science and Engineering, the report says. The project targets MHC class II-mediated immune responses, which the participants describe as complex and less understood, with no systematic method yet established for designing and optimising neoantigen candidates. That is a statement of the problem, not a result.

Both items sit inside a broader institutional push. The US Department of Energy released its SCAC Quantum Committee Report, a roadmap toward demonstrating a scientifically relevant, error-corrected quantum computer by 2028 and a long-term vision for a dedicated Quantum Computing User Facility. Fermilab's write-up says the subcommittee was chaired by Fermilab CTO Anna Grassellino, with University of Chicago professor Supratik Guha as vice chair, and drew on hundreds of contributors across the US quantum ecosystem. The report's stated shift is to measure success by scientific utility rather than hardware metrics alone.

Hardware results keep arriving faster than deployments

The research pipeline is moving too. On 1 October, ScienceDaily reported that University of Surrey researchers proposed a qubit design based on superfluid helium-3, published in npj Quantum Information, with calculations suggesting error rates around 100 times lower than conventional superconducting qubits. Lead author Priya Sharma said the maths “tells us that it should work” and that the next step is a prototype. No prototype exists yet.

Other recent results are experimental. A Duke Quantum Center-led team simulated string breaking on a 13-ion quantum simulator, published 23 September in Nature Physics, with Christopher Monroe saying quantum simulation is the best available platform short of witnessing the Big Bang. Separately, a UChicago PME, Harvard, Stony Brook and Quantinuum collaboration demonstrated a universal gate set using non-Abelian anyons on 54 qubits of Quantinuum's H2 processor, published in Nature. Kyoto and Hiroshima researchers reported an entangled measurement for 3-photon W states, 25 years after the equivalent for GHZ states, per ScienceDaily on 29 September.

Commercial and infrastructure news is thinner and mostly forward-looking. General Compute signed a multi-year agreement on 2 October to offer Cerebras wafer-scale hardware from Q1 2027, with value and scale undisclosed, DataCenterDynamics reported. Quantum Space executed a launch processing work order with All Points Logistics on 30 September for its Prime mission, targeting the second half of 2027.

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Sources

10
  1. 01IBM Expands Research Partnerships in India for AI and Quantum ComputingEN
  2. 02Japan Backs Quantum Computing Project for Cancer Immunotherapy ResearchEN
  3. 03DOE releases national quantum computing roadmap following field-wide effort led by SCAC subcommitteeEN
  4. 04This new qubit could be 100 times less error-prone in superfluid quantum computer breakthroughEN
  5. 05Quantum computer simulates matter “popping into existence”EN
  6. 06Quantum computing's “dark horse” just proved it can go universalEN
  7. 07Quantum teleportation breakthrough: Scientists crack a 25-year entanglement challengeEN
  8. 08General Compute signs multi-year agreement with CerebrasEN
  9. 09Quantum Space Executes Launch Processing Agreement with All Points Logistics for Prime MissionEN
  10. 10Argonne: Building Scientific Computing Ecosystems for AI-Enabled DiscoveryEN

All figures and quotations in this text come from the sources listed below.

Content prepared by the editorial team with AI assistance.

Grace Okonkwo

Grace Okonkwo

AI, models and technology

Grace Okonkwo covers AI, models and technology for FLASH24, working from primary sources such as model cards, API documentation and benchmark papers rather than vendor summaries. She checks training data provenance, evaluation conditions and reported scores against the underlying datasets before any figure reaches print. She interviews researchers and engineers directly, tracks release calendars from major labs, and compares successive model versions on the same tests. Her own self-hosting, home-network and documentation-reading habits feed straight into that desk, since she tests tools on her own hardware first. She does not publish benchmark claims without a reproducible method.

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