153 citations · 232 across the 13 of their papers we have counts for
13 papers
Sequential Reservoir Computing for Efficient High-Dimensional Spatiotemporal Forecasting
Ata Akbari Asanjan, Filip Wudarski, Daniel O'Connor +4
Forecasting high-dimensional spatiotemporal systems remains computationally challenging for recurrent neural networks (RNNs) and long short-term memory (LSTM) models due to gradien…
The USRA Feynman Quantum Academy: If You Give a Student a Quantum Internship
Zoe Gonzalez Izquierdo, Sophie Block, Besart Mujeci +3
In the rapidly expanding field of quantum computing, one key aspect to maintain ongoing progress is ensuring that early career scientists interested in the field get appropriate gu…
Pushing the Boundary of Quantum Advantage in Hard Combinatorial Optimization with Probabilistic Computers
Shuvro Chowdhury, Navid Anjum Aadit, Andrea Grimaldi +12
Recent demonstrations on specialized benchmarks have reignited excitement for quantum computers, yet whether they can deliver an advantage for practical real-world problems remains…
How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits
Masoud Mohseni, Artur Scherer, K. Grace Johnson +48
In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become po…
A Multilevel Approach For Solving Large-Scale QUBO Problems With Noisy Hybrid Quantum Approximate Optimization
Filip B. Maciejewski, Bao Gia Bach, Maxime Dupont +5
Quantum approximate optimization is one of the promising candidates for useful quantum computation, particularly in the context of finding approximate solutions to Quadratic Uncons…
Combinatorial Reasoning: Selecting Reasons in Generative AI Pipelines via Combinatorial Optimization
Mert Esencan, Tarun Advaith Kumar, Ata Akbari Asanjan +5
Recent Large Language Models (LLMs) have demonstrated impressive capabilities at tasks that require human intelligence and are a significant step towards human-like artificial inte…
Hybrid quantum-classical reservoir computing for simulating chaotic systems
Filip Wudarski, Daniel O`Connor, Shaun Geaney +5
Forecasting chaotic systems is a notably complex task, which in recent years has been approached with reasonable success using reservoir computing (RC), a recurrent network with fi…
Design and execution of quantum circuits using tens of superconducting qubits and thousands of gates for dense Ising optimization problems
Filip B. Maciejewski, Stuart Hadfield, Benjamin Hall +13
We develop a hardware-efficient ansatz for variational optimization, derived from existing ansatze in the literature, that parametrizes subsets of all interactions in the Cost Hami…
Anomaly Detection in Aeronautics Data with Quantum-compatible Discrete Deep Generative Model
Thomas Templin, Milad Memarzadeh, Walter Vinci +4
Deep generative learning cannot only be used for generating new data with statistical characteristics derived from input data but also for anomaly detection, by separating nominal…
Quantum-Enhanced Greedy Combinatorial Optimization Solver
Maxime Dupont, Bram Evert, Mark J. Hodson +13
Combinatorial optimization is a broadly attractive area for potential quantum advantage, but no quantum algorithm has yet made the leap. Noise in quantum hardware remains a challen…
RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputs
Michael Niemeyer, Jonathan T. Barron, Ben Mildenhall +3
Neural Radiance Fields (NeRF) have emerged as a powerful representation for the task of novel view synthesis due to their simplicity and state-of-the-art performance. Though NeRF c…
Practical Verification of Quantum Properties in Quantum Approximate Optimization Runs
M. Sohaib Alam, Filip A. Wudarski, Matthew J. Reagor +7
In order to assess whether quantum resources can provide an advantage over classical computation, it is necessary to characterize and benchmark the non-classical properties of quan…
Scaling advantage in quantum simulation of geometrically frustrated magnets
Andrew D. King, Jack Raymond, Trevor Lanting +51
The promise of quantum computing lies in harnessing programmable quantum devices for practical applications such as efficient simulation of quantum materials and condensed matter s…