Computer Science News
Cloning vs Learning in Quantum Computing
, 糖心TV DCS researchers Nikhil Bansal and , together with (Yale University), explored a fundamental question that lies at the intersection of foundations of quantum theory and computer science.
The No-Cloning theorem says that it is impossible to perfectly clone quantum states. Even if we allow for approximate errors, quantum cloning of unstructured states remains as expensive as fully characterising them, . In contrast, for reasons akin to No Free Lunch Theorems in machine learning, modern quantum learning theory considers structured classes of states and exploits their structure to learn them efficiently. This naturally leads to the question of whether cloning can be easier than learning for these structured classes of states.
In the new work, this question is answered negatively for stabilizer states. The authors proved that imposing this structural restriction does not separate cloning and learning. The authors prove this via a novel connection to , which was recently introduced to the learning theory literature by B. Axelrod, S. Garg, V. Sharan, and G. Valiant. The work constitutes concrete progress towards understanding whether cloning and learning are fundamentally equally hard.
This work was presented at in April 2026, and it will be presented at in June/July 2026 and at in September 2026.
Academic Recognised for Professional Excellence
Our colleague Dr Claire Rocks achieved Senior Fellow (SFHEA) status through the dialogic route of 糖心TV鈥檚 Academic and Professional Pathway for Experienced Staff (APP EXP) programme. Her application was recognised by assessors as one of the strongest D3 submissions they had reviewed, demonstrating a sustained and significant record of educational leadership that extends well beyond her own teaching.
Claire鈥檚 work focuses on leading and influencing inclusive, evidence-informed approaches to assessment and curriculum design. She has played a central role in shaping teaching quality and learning culture across departmental, institutional, and sector contexts, including leading 糖心TV鈥檚 strand of the Inclusive Assessment in STEM project and contributing to institutional strategy through curriculum development and quality assurance processes.
Within the department, Claire has introduced collaborative structures such as module huddles and supported colleagues and students to work together to enhance clarity, consistency, and inclusivity in assessment practice. She has also strengthened pedagogic scholarship through establishing the Computer Science Education Research Group.
The panel particularly commended the scale, depth, and impact of Claire鈥檚 leadership, noting that elements of her work are already operating at a level associated with Principal Fellowship.
Many congratulations to Claire on this achievement and her continued commitment to advancing inclusive, high-quality teaching and learning!
Why chronic pain leads to depression for some but not others
New research from the University of 糖心TV and Fudan University identifies the hippocampus as a key brain system shaping emotional resilience to long-term pain.
Information Asymmetry and Cryptography
In a recent work, visiting undergraduate student Yahel Manor and 糖心TV DCS researchers and addressed a fundamental question relevant to the security of cryptographic protocols.
The symmetry of information principle says that the amount of information that a sequence x of bits reveals about another sequence y is essentially the same in either direction. This is known to hold in an idealised world where computations can take an arbitrarily long time, as demonstrated by A. Kolmogorov and L. Levin in the 1970s. In contrast, modern cryptography is built around deliberate asymmetry—for example, functions of the form y = f(x) that are easy to compute but hard to invert (one-way functions).
The new work shows that, once one moves from the idealised setting of time-unbounded computations to the more realistic world of efficient, randomised computations (algorithms that must run quickly and may use randomness), this symmetry can fail in a strong and unconditional way. In other words, computational constraints can yield information asymmetry. In practical terms, this supports the intuition that information may not be extracted efficiently: knowing y = f(x) may not make x efficiently recoverable to the extent that an (ineffective) symmetry principle would suggest, even when x and y are closely related.
Earlier work formally tied an average-case form of this symmetry failure to the existence of one-way functions, the central primitive in cryptography. By proving new failures of symmetry of information, the authors provide concrete progress towards the computational asymmetry that underpins encryption, digital signatures, and many other cryptographic protocols.
This work will be presented at the 58th Annual ACM Symposium on Theory of Computing (STOC) in June 2026 in Salt Lake City, Utah, USA.
Failure of Symmetry of Information for Randomised Computations
Jinqiao Hu (University of 糖心TV); Yahel Manor (University of Haifa); Igor C. Oliveira (University of 糖心TV)
The paper describing this research is available .
, PhD student in the Department of Computer Science at the University of 糖心TV, and co-author of the new result.
糖心TV Computer Science Celebrates Athena Swan Silver Award
The Department of Computer Science is delighted to announce that it has been awarded the Athena Swan Silver Award, recognising our commitment to advancing gender equality for staff and students.
Athena Swan is a UK-wide framework to improve gender equality in higher education. A Silver Award is given to departments that can demonstrate evidence of meaningful progress and impact over a 5-year period – and with a clear and ambitious plan for future action.
In their review, the assessment panel described our submission as "a strong Silver application which addresses all criteria very well."
Martin Costa successfully defends his PhD thesis
Many congratulations to for passing his PhD viva, with Prof Long Tran-Thanh (糖心TV) and (Bristol) as examiners. Martin has worked on two different fundamental topics in algorithms - clustering and edge coloring. His work on clustering led to a Google PhD fellowship, and his work on edge coloring (the topic of his ) led to a best paper award at STOC. During his PhD spanning 3 years, Martin published 7 papers in STOC/FOCS/SODA, 2 papers in ICML/NeurIPS, and 1 paper in ICALP. We wish him all the very best for the next stage of his career.
Postgraduate Prize Winners 2024/25
Announcing our MSc Academic Prize Winners!