Seminars
From Harmonic Oscillators to Quantum Chromodynamics and Superstring Theory
Speaker: Masanori Hanada
Affiliation: QMUL
Date: 8 October 2026
Abstract: According to Sidney Coleman, "the career of a young theoretical physicist consists of treating the harmonic oscillator in ever-increasing levels of abstraction." So, obviously, the first physics model we should study on a quantum computer is the harmonic oscillator. But what can we learn from there? We show that a wide class of physics models of interest, including quantum field theories such as Yang-Mills theory and its variants, including Quantum Chromodynamics (QCD) and super Yang-Mills theory, or matrix models dual to superstring/M-theory, can be studied using the same simulation techniques as those for harmonic oscillators.
Historically, simulating Yang-Mills theory on quantum computers has faced significant challenges --- namely, it is impossible to design efficient quantum circuits, even on fault-tolerant universal computers --- because the Kogut-Susskind (KS) Hamiltonian formulation was used without a deep reason; everyone used it simply because everyone else did. In fact, we can take a slightly different approach, motivated by the so-called Banks-Fischler-Shenker-Susskind (BFSS) matrix model and orbifold-lattice Hamiltonian formulated by Kaplan, Katz, and Unsal (KKU). This solves the bottleneck of the KS approach rather trivially.
Specifically, the KS approach is challenging because it is immensely hard to describe the polar coordinate on quantum devices, while the BFSS/KKU approach is straightforward because it uses Cartesian coordinates, which is essentially a collection of harmonic oscillators. Quantum circuits for SU(N) Yang-Mills theory on arbitrary dimensions and with arbitrary matter content can be written explicitly, using only CNOT gates and one-qubit rotations, at arbitrary truncation level --- which is out of reach in other approaches --- without using any complicated math beyond the Fourier transform. Because both approaches provide the same continuum limit, we can simply take the one suitable for quantum simulations.
Quantum Computing for Particle Physics: Simulation and Machine Learning
Date: 1 July 2026
Speaker: Callum Duffy (UCL)
Abstract: Quantum computing is a rapidly emerging technology with potential applications in particle physics. From the direct simulation of quantum field theories on quantum hardware to the acceleration of computationally demanding components of data analysis, the interface between quantum information science and high-energy physics has become an active and expanding area of research.
Potential applications include the quantum simulation of lattice gauge theories and real-time quantum dynamics, as well as hybrid quantum–classical algorithms for optimisation, sampling, and data-driven analysis in collider and phenomenological studies. Although current devices remain in the noisy intermediate-scale quantum (NISQ) era and are limited in scale and noise resilience, this period provides an important testing ground for developing algorithms for future large-scale quantum machines.
This talk will provide a high-level and accessible introduction to quantum computing, with particular emphasis on quantum machine learning. I will discuss two complementary perspectives. First, the use of parameterised quantum circuits as trainable machine learning models, with potential applications to data analysis; and second, the use of classical machine learning techniques to design and control quantum systems, for example, through quantum optimal control methods aimed at improving quantum simulation. I will outline potential advantages, discuss current limitations and realistic near-term expectations, and highlight recent contributions from our group in these areas.
A Quantum Field Theory Approach to Entanglement Measures
Date: 2 June 2026
Speaker: Olalla A. Castro-Alvaredo (Department of Mathematics)
Abstract: In this talk I will introduce some of my research of the past 20 years, which deals with functions known as Entanglement Measures. I will define some of these measures, starting with the fundamental concept of a reduced density matrix and mention some of their properties and differences between different measures. I will motivate why they are of such interest to so many interconnected areas, from Applied Mathematics to Theoretical Physics , Numerical Simulations and Information Theory.
I will then explain what is special about Quantum Field Theory, present some of the computational methods that are specific to QFT in 1+1 D, particularly the use of branch point twist fields that I co-pioneered and is now widespread in this area. I will show some of the most famous results that follow from these approaches and give an indication of the current state of the art.
Quantum and Classical Algorithms (Newton vs Grover)
Date: 19 May 2026
Speaker: Mansur (University of Mesina, Italy)
Leveraging Quantum Hardware for Fundamental Physics
Date: 28 April 2026
Speaker: Jack Araz (Group Director/Department of Engineering)
Abstract: Recent advances in quantum hardware and quantum information science are opening new avenues for tackling longstanding challenges in fundamental physics. Quantum technologies are expected to assist in various areas of particle physics, from discovering new particles to enabling first-principles calculations in QCD. In this talk, I will discuss how emerging quantum platforms can be utilised to simulate aspects of the Standard Model.
A particular focus will be on trapped ion quantum computers, which offer a unique capability: they can naturally represent both fermionic and bosonic degrees of freedom within the same device, using ion spins as qubits and collective vibrational modes as continuous variables. This hybrid simulation approach can go beyond the reach of current superconducting quantum technologies. Furthermore, we will explore how quantum optimal control and quantum hardware architecture design can be employed to enhance our ability to simulate lattice field theories.