590 citations · 4.9k across the 34 of their papers we have counts for
34 papers
Multivariate quantum state preparation with optimized tensor networks
Matthew L. Sims-Goh, Lukasz Cincio, Annina Z. Lieberherr +2
Quantics tensor trains are attracting intense interest for quantum-inspired computing and quantum state preparation. These methods, which approximate continuum functions by represe…
Fullqubit alchemist: Quantum algorithm for alchemical free energy calculations
Po-Wei Huang, Gregory Boyd, Gian-Luca R. Anselmetti +11
Accurately computing the free energies of biological processes is a cornerstone of computer-aided drug design, but it is a daunting task. The need to sample vast conformational spa…
Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning
Vladimir Skavysh, Sofia Priazhkina, Diego Guala +1
Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. We are the first to study whether Quantum Monte Carlo (QMC) al…
Fast quantum circuit cutting with randomized measurements
Angus Lowe, Matija Medvidović, Anthony Hayes +4
We propose a new method to extend the size of a quantum computation beyond the number of physical qubits available on a single device. This is accomplished by randomly inserting me…
Quantum computing with differentiable quantum transforms
Olivia Di Matteo, Josh Izaac, Tom Bromley +6
We present a framework for differentiable quantum transforms. Such transforms are metaprograms capable of manipulating quantum programs in a way that preserves their differentiabil…
Quantum circuits with many photons on a programmable nanophotonic chip
J. M. Arrazola, V. Bergholm, K. Brádler +36
Growing interest in quantum computing for practical applications has led to a surge in the availability of programmable machines for executing quantum algorithms. Present day photo…
Estimating the gradient and higher-order derivatives on quantum hardware
Andrea Mari, Thomas R. Bromley, Nathan Killoran
For a large class of variational quantum circuits, we show how arbitrary-order derivatives can be analytically evaluated in terms of simple parameter-shift rules, i.e., by running…
Applications of Near-Term Photonic Quantum Computers: Software and Algorithms
Thomas R. Bromley, Juan Miguel Arrazola, Soran Jahangiri +7
Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Recent efforts have led to the discovery of GBS algorithms with applications to graph-based pr…
Transfer learning in hybrid classical-quantum neural networks
Andrea Mari, Thomas R. Bromley, Josh Izaac +2
We extend the concept of transfer learning, widely applied in modern machine learning algorithms, to the emerging context of hybrid neural networks composed of classical and quantu…
Demonstrating quantum coherence and metrology that is resilient to transversal noise
Chao Zhang, Thomas R. Bromley, Yun-Feng Huang +7
Quantum systems can be exploited for disruptive technologies but in practice quantum features are fragile due to noisy environments. Quantum coherence, a fundamental such feature,…
PennyLane: Automatic differentiation of hybrid quantum-classical computations
Ville Bergholm, Josh Izaac, Maria Schuld +65
PennyLane is a Python 3 software framework for differentiable programming of quantum computers. The library provides a unified architecture for near-term quantum computing devices,…
Classical benchmarking of Gaussian Boson Sampling on the Titan supercomputer
Brajesh Gupt, Juan Miguel Arrazola, Nicolás Quesada +1
Gaussian Boson Sampling is a model of photonic quantum computing where single-mode squeezed states are sent through linear-optical interferometers and measured using single-photon…
Photonic quantum algorithm for Monte Carlo integration
Patrick Rebentrost, Brajesh Gupt, Thomas R. Bromley
We present a continuous-variable photonic quantum algorithm for the Monte Carlo evaluation of multi-dimensional integrals. Our algorithm encodes n-dimensional integration into n+3…
Machine learning method for state preparation and gate synthesis on photonic quantum computers
Juan Miguel Arrazola, Thomas R. Bromley, Josh Izaac +3
We show how techniques from machine learning and optimization can be used to find circuits of photonic quantum computers that perform a desired transformation between input and out…
Continuous-variable quantum neural networks
Nathan Killoran, Thomas R. Bromley, Juan Miguel Arrazola +3
We introduce a general method for building neural networks on quantum computers. The quantum neural network is a variational quantum circuit built in the continuous-variable (CV) a…
Quantum computational finance: Monte Carlo pricing of financial derivatives
Patrick Rebentrost, Brajesh Gupt, Thomas R. Bromley
Financial derivatives are contracts that can have a complex payoff dependent upon underlying benchmark assets. In this work, we present a quantum algorithm for the Monte Carlo pric…
Quantum approximate optimization with Gaussian boson sampling
Juan Miguel Arrazola, Thomas R. Bromley, Patrick Rebentrost
Hard optimization problems are often approached by finding approximate solutions. Here, we highlight the concept of proportional sampling and discuss how it can be used to improve…
Using Gaussian Boson Sampling to Find Dense Subgraphs
Juan Miguel Arrazola, Thomas R. Bromley
Boson sampling devices are a prime candidate for exhibiting quantum supremacy, yet their application for solving problems of practical interest is less well understood. Here we sho…
Batched quantum state exponentiation and quantum Hebbian learning
Thomas R. Bromley, Patrick Rebentrost
Machine learning is a crucial aspect of artificial intelligence. This paper details an approach for quantum Hebbian learning through a batched version of quantum state exponentiati…
Accessible bounds for general quantum resources
Thomas R. Bromley, Marco Cianciaruso, Sofoklis Vourekas +2
The recent development of general quantum resource theories has given a sound basis for the quantification of useful quantum effects. Nevertheless, the evaluation of a resource mea…
Quantum Hopfield neural network
Patrick Rebentrost, Thomas R. Bromley, Christian Weedbrook +1
Quantum computing allows for the potential of significant advancements in both the speed and the capacity of widely used machine learning techniques. Here we employ quantum algorit…
Certification and Quantification of Multilevel Quantum Coherence
Martin Ringbauer, Thomas R. Bromley, Marco Cianciaruso +6
Quantum coherence, present whenever a quantum system exists in a superposition of multiple classically distinct states, marks one of the fundamental departures from classical physi…
Converting multilevel nonclassicality into genuine multipartite entanglement
Bartosz Regula, Marco Piani, Marco Cianciaruso +3
Characterizing genuine quantum resources and determining operational rules for their manipulation are crucial steps to appraise possibilities and limitations of quantum technologie…
An introduction to quantum discord and non-classical correlations beyond entanglement
Gerardo Adesso, Marco Cianciaruso, Thomas R. Bromley
In this didactic article we explore the concept of quantum correlations beyond entanglement. We begin by introducing and motivating the classically correlated states and then showi…