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Pulsar Classification: Comparing Quantum Convolutional Neural Networks and Quantum Support Vector Machines
Donovan Slabbert, Matt Lourens, Francesco Petruccione
Well-known quantum machine learning techniques, namely quantum kernel assisted support vector machines (QSVMs) and quantum convolutional neural networks (QCNNs), are applied to the…
Noninvertibility and non-Markovianity of quantum dynamical maps
Vinayak Jagadish, R. Srikanth, Francesco Petruccione
We identify two broad types of noninvertibilities in quantum dynamical maps, one necessarily associated with CP indivisibility and one not so. We study the production of (non-)Mark…
Conservation Laws for a Thermal Reservoir Model in Open Quantum Systems
Muhammad Al-Zafar Khan, Mervlyn Moodley, Francesco Petruccione
We construct Lie point symmetries, a closed-form solution and conservation laws using a non-Noetherian approach for a specific case of the Gorini-Kossakowski-Sudarshan-Lindblad equ…
Petz recovery maps for qudit quantum channels
Lea Lautenbacher, Vinayak Jagadish, Francesco Petruccione +1
This study delves into the efficacy of the Petz recovery map within the context of two paradigmatic quantum channels: dephasing and amplitude-damping. While prior investigations ha…
Cyclic quantum engines enhanced by strong bath coupling
Camille L. Latune, Graeme Pleasance, Francesco Petruccione
While strong system-bath coupling produces rich and interesting phenomena, applications to quantum thermal engines have been so far pointing mainly at detrimental effects. The deli…
Hybrid Genetic Optimisation for Quantum Feature Map Design
Rowan Pellow-Jarman, Anban Pillay, Ilya Sinayskiy +1
Kernel methods are an important class of techniques in machine learning. To be effective, good feature maps are crucial for mapping non-linearly separable input data into a higher…
Classical Ensembles of Single-Qubit Quantum Variational Circuits for Classification
Shane McFarthing, Anban Pillay, Ilya Sinayskiy +1
The quantum asymptotically universal multi-feature (QAUM) encoding architecture was recently introduced and showed improved expressivity and performance in classifying pulsar stars…
Digital Simulation of Single Qubit Markovian Open Quantum Systems: A Tutorial
I J David, I Sinayskiy, F Petruccione
One of the first proposals for the use of quantum computers was the simulation of quantum systems. Over the past three decades, great strides have been made in the development of a…
Statistical and machine learning approaches for prediction of long-time excitation energy transfer dynamics
Kimara Naicker, Ilya Sinayskiy, Francesco Petruccione
One of the approaches used to solve for the dynamics of open quantum systems is the hierarchical equations of motion (HEOM). Although it is numerically exact, this method requires…
Hierarchical quantum circuit representations for neural architecture search
Matt Lourens, Ilya Sinayskiy, Daniel K. Park +2
Machine learning with hierarchical quantum circuits, usually referred to as Quantum Convolutional Neural Networks (QCNNs), is a promising prospect for near-term quantum computing.…
Markovian Noise Modelling and Parameter Extraction Framework for Quantum Devices
Dean Brand, Ilya Sinayskiy, Francesco Petruccione
In recent years, Noisy Intermediate Scale Quantum (NISQ) computers have been widely used as a test bed for quantum dynamics. This work provides a new hardware-agnostic framework fo…
Compact quantum kernel-based binary classifier
Carsten Blank, Adenilton J. da Silva, Lucas P. de Albuquerque +2
Quantum computing opens exciting opportunities for kernel-based machine learning methods, which have broad applications in data analysis. Recent works show that quantum computers c…
Measure of invertible dynamical maps under convex combinations of noninvertible dynamical maps
Vinayak Jagadish, R. Srikanth, Francesco Petruccione
We study the convex combinations of the generalized Pauli dynamical maps in a Hilbert space of dimension . For certain choices of the decoherence function, the maps are…
Machine learning for excitation energy transfer dynamics
Kimara Naicker, Ilya Sinayskiy, Francesco Petruccione
A well-known approach to describe the dynamics of an open quantum system is to compute the master equation evolving the reduced density matrix of the system. This approach plays an…
Noninvertibility as a requirement for creating a semigroup under convex combinations of channels
Vinayak Jagadish, R. Srikanth, Francesco Petruccione
We study the conditions under which a semigroup is obtained upon convex combinations of channels. In particular, we study the set of Pauli and generalized Pauli channels. We find t…
Near Term Algorithms for Linear Systems of Equations
Aidan Pellow-Jarman, Ilya Sinayskiy, Anban Pillay +1
Finding solutions to systems of linear equations is a common prob\-lem in many areas of science and engineering, with much potential for a speedup on quantum devices. While the Har…
Pseudomode description of general open quantum system dynamics: non-perturbative master equation for the spin-boson model
Graeme Pleasance, Francesco Petruccione
We outline a non-perturbative approach for simulating the behavior of open quantum systems interacting with a bosonic environment defined by a generalized spectral density function…
Digital simulation of convex mixtures of Markovian and non-Markovian single qubit Pauli channels on NISQ devices
I J David, I Sinayskiy, F Petruccione
Quantum algorithms for simulating quantum systems provide a clear and provable advantage over classical algorithms in fault-tolerant settings. There is also interest in quantum alg…
Configurable sublinear circuits for quantum state preparation
Israel F. Araujo, Daniel K. Park, Teresa B. Ludermir +3
The theory of quantum algorithms promises unprecedented benefits of harnessing the laws of quantum mechanics for solving certain computational problems. A persistent obstacle to us…
A Comparison of Various Classical Optimizers for a Variational Quantum Linear Solver
Aidan Pellow-Jarman, Ilya Sinayskiy, Anban Pillay +1
Variational Hybrid Quantum Classical Algorithms (VHQCAs) are a class of quantum algorithms intended to run on noisy intermediate-scale quantum (NISQ) devices. These algorithms empl…
Robust quantum classifier with minimal overhead
Daniel K. Park, Carsten Blank, Francesco Petruccione
To witness quantum advantages in practical settings, substantial efforts are required not only at the hardware level but also on theoretical research to reduce the computational co…
Initial entanglement, entangling unitaries, and completely positive maps
Vinayak Jagadish, R. Srikanth, Francesco Petruccione
The problem of conditions on the initial correlations between the system and the environment that lead to completely positive (CP) or not-completely positive (NCP) maps has been st…
Circuit-based quantum random access memory for classical data with continuous amplitudes
Tiago M. L. de Veras, Ismael C. S. de Araujo, Daniel K. Park +1
Loading data in a quantum device is required in several quantum computing applications. Without an efficient loading procedure, the cost to initialize the algorithms can dominate t…
Quantum-enhanced analysis of discrete stochastic processes
Carsten Blank, Daniel K. Park, Francesco Petruccione
Discrete stochastic processes (DSP) are instrumental for modelling the dynamics of probabilistic systems and have a wide spectrum of applications in science and engineering. DSPs a…