Reports, Conferences & Other Outputs

Conference papers, books, reports, and miscellaneous scholarly outputs.

Journal Articles Preprints Reports, Conferences & Other Outputs

Publications

99 total

19 results matching your filters

02 Nov 2025conference
Quantum Neuromorphic Classification of EEG Brain Signals

2025 IEEE International Conference on Quantum Artificial Intelligence (QAI)

Dr Dean BrandRavi Kumar Jha

Quantum computing has recently inspired many applications in machine learning. In this paper, we present a novel idea of combining neuromorphic computing and quantum computing to develop an advanced application for studying and analysing brain signals. We integrate a quantum spiking leaky integrate-and-fire (QLIF) neuron into a 3D spiking neural network framework designed for analysing and classifying biological data. This modified model is applied to EEG brain signals obtained from experimental measurements of a subject's wrist movements, providing a real-world demonstration of the model's capabilities. The proof-of-concept results show that the QLIF model outperforms its classical counterpart across a series of binary classification tasks, suggesting the promising compatibility of quantum neuromorphic algorithms for the spatio-temporal EEG dataset. Our illustration offers a new direction for ...

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21 Mar 2025conference
Automated Quantum Algorithm Design via Evolutionary Search and Hierarchical Quantum Circuit Representation

SMT 2025

Quantum algorithms are inherently modular and often exhibit repeating patterns. We exploit this by utilizing a hierarchical quantum circuit representation [1] in conjunction with evolutionary search for the automated design of such algorithms. In this representation, quantum circuits are abstracted beyond the usual gate-sequence description and scale automatically to any circuit size. This allows us to evaluate a single candidate algorithm on varying problem sizes, which enables global features such as the optimal number of repetitions and parameter relationships to be learnt. We present our method as a general tool that uses techniques from Neural Architecture Search and discuss its performance compared to an exhaustive search. Remarkably, we are able to rediscover three well known quantum algorithms, the Quantum Fourier Transform, Deutsch-Jozsa and Grover's search.[1] Lourens, M., Sinayskiy, I., Park, D ...

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21 Mar 2025conference
Generating Low-Dimensional and Scale-Invariant Ansatzes for Interacting Quantum Many-Body States

SMT 2025

Matt LourensIlya SinayskiyJohannes KrielProf. Francesco Petruccione

We present a method for generating low-dimensional ansatzes to obtain mean-field-like theories that incorporate correlations in physical systems. Our technique employs an evolutionary algorithm exploiting a hierarchical and scale-invariant compute-graph [1] to find low-energy states of a given Hamiltonian. This representation helps realize physical symmetries and enables generalization over increasing numbers of degrees of freedom, resulting in a low-dimensional ansatz capturing the fundamental aspects of a model. Remarkably, we find analytically tractable ansatzes with a degree of universality that encode correlations, capture finite-size effects, provide accurate ground state energy predictions and offer a more precise description of critical phenomena. We demonstrate this method on the quantum transverse field Ising model (TFIM) and the Lipkin-Meshkov-Glick (LMG) model, where the same ansatz was ...

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15 Jul 2024conference
A Six-Core Microstructured Fiber for Sensing Applications

Laser Applications to Chemical, Security and Environmental Analysis

Akshat AgarwalShweta MittalSushma PuniaAnkur SahariaAnton V BourdineOleg G MorozovIvan K MeshkovDr Yaseera IsmailGhanshyam SinghManish Tiwari

A surface plasmon resonance biosensor design is presented, comprising of gold-coated six-core microstructured fiber. The designed sensor exhibits phase matching characteristics for a wider refractive index range of 1.37-1.41.

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24 May 2024conference
Quantum Circuit Optimisation For The Quantum Simulation Of Markovian Open Quantum Systems

QTML 2024

IJ DavidI SinayskiyProf. Francesco Petruccione

One of the first proposed applications of quantum computers was for the simulation of physical systems, as suggested by Y. Manin and RP Feynman [1, 2]. Over the last three decades there have been many advances in simulating quantum systems with quantum computers [3]. Although many of the advances made have only been for the simulation of closed quantum systems (Hamiltonian simulation), fewer advances have been made in developing algorithms to simulate Open Quantum Systems (OQS)[4, 5, 6]. In this work we will focus on the simulation of Markovian OQS, which means OQS which can be described by a master equation that is in the GKSL (Gorini-Kossakowski-Sudarshan-Lindblad) form [7, 8]. The central approach in the quantum simulation of OQS involves finding novel ways to compile a quantum channel Et such that for a given GKSL generator L, an evolution time t≥ 0, a precision󰂃> 0 and a distance measure dist (·,·) such that for any input state ρ, dist (eLtρ, Et (ρ))≤󰂃,(1) which means that Et approximates etL to a precision󰂃. The most common way to compile the channel Et is to use Trotter-Suzuki (TS) product formulas but there are also other methods such as randomised product formulas and QDRIFT channels which can be used to compile the channel Et. In all of these strategies one requires an optimal gate complexity and error so as to have efficient simulation. Usually when one obtains bounds on the error and gate complexity it is obtained for the worst-case however this may be a gross overestimate of the error and gate complexity. Recently, the proposed use of the average error computed over an ensemble of random input ...

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12 Mar 2024conference
HEK293/ACE2 cells' response to severe acute respiratory syndrome coronavirus-2 infection and low-level-laser therapy under microscopy

Mechanisms of Photobiomodulation Therapy XVIII

Luleka MngwengweMasixole Y LugongoloSaturnin Ombinda-LemboumbaDr Yaseera IsmailPatience Mthunzi-Kufa

Low-level laser therapy (LLLT) is a method of exposing cells or tissue to low levels of red and near-infrared light that has a high success rate for the treatment of various ailments. LLLT has been used to treat various diseases, including wounds, spinal cord injuries, and symptoms of viral conditions like blisters caused by the Herpes Simplex Virus. The aims of the study are to investigate the effect of laser irradiation on SARS-CoV-2 infected cells and on uninfected cells using a scanning electron microscope (SEM) and transmission electron microscopy (TEM) as analysis tools. SEM was used to determine the morphological differences caused by laser irradiation on SARS-CoV-2 infected HEK293/ACE2 cells as well as non-irradiated SARS-CoV-2 infected ones. In addition, the results obtained were compared to irradiated and non-irradiated uninfected cells. To further evaluate the effect of irradiation and SARS-CoV-2 ...

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