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Efficient quantum computation of molecular forces and other energy gradients
Thomas E. O'Brien, Michael Streif, Nicholas C. Rubin +12
While most work on the quantum simulation of chemistry has focused on computing energy surfaces, a similarly important application requiring subtly different algorithms is the comp…
Quantum Model Learning Agent: characterisation of quantum systems through machine learning
Brian Flynn, Antonio Andreas Gentile, Nathan Wiebe +2
Accurate models of real quantum systems are important for investigating their behaviour, yet are difficult to distill empirically. Here, we report an algorithm -- the Quantum Model…
Quantum Error Correction with Gauge Symmetries
Abhishek Rajput, Alessandro Roggero, Nathan Wiebe
Quantum simulations of Lattice Gauge Theories (LGTs) are often formulated on an enlarged Hilbert space containing both physical and unphysical sectors in order to retain a local Ha…
EQC : Ensembled Quantum Computing for Variational Quantum Algorithms
Samuel Stein, Yufei Ding, Nathan Wiebe +5
Variational quantum algorithm (VQA), which is comprised of a classical optimizer and a parameterized quantum circuit, emerges as one of the most promising approaches for harvesting…
Nearly Optimal Quantum Algorithm for Estimating Multiple Expectation Values
William J. Huggins, Kianna Wan, Jarrod McClean +3
Many quantum algorithms involve the evaluation of expectation values. Optimal strategies for estimating a single expectation value are known, requiring a number of state preparatio…
Hybridized Methods for Quantum Simulation in the Interaction Picture
Abhishek Rajput, Alessandro Roggero, Nathan Wiebe
Conventional methods of quantum simulation involve trade-offs that limit their applicability to specific contexts where their use is optimal. In particular, the interaction picture…
Quantum Generative Training Using Rényi Divergences
Maria Kieferova, Ortiz Marrero Carlos, Nathan Wiebe
Quantum neural networks (QNNs) are a framework for creating quantum algorithms that promises to combine the speedups of quantum computation with the widespread successes of machine…
Fault-Tolerant Quantum Simulations of Chemistry in First Quantization
Yuan Su, Dominic W. Berry, Nathan Wiebe +2
Quantum simulations of chemistry in first quantization offer important advantages over approaches in second quantization including faster convergence to the continuum limit and the…
Quantum Machine Learning with SQUID
Alessandro Roggero, Jakub Filipek, Shih-Chieh Hsu +1
In this work we present the Scaled QUantum IDentifier (SQUID), an open-source framework for exploring hybrid Quantum-Classical algorithms for classification problems. The classical…
Real time evolution for ultracompact Hamiltonian eigenstates on quantum hardware
Katherine Klymko, Carlos Mejuto-Zaera, Stephen J. Cotton +9
In this work we present a detailed analysis of variational quantum phase estimation (VQPE), a method based on real-time evolution for ground and excited state estimation on near-te…
Experimental statistical signature of many-body quantum interference
Taira Giordani, Fulvio Flamini, Matteo Pompili +8
Multi-particle interference is an essential ingredient for fundamental quantum mechanics phenomena and for quantum information processing to provide a computational advantage, as r…
Simulating Effective QED on Quantum Computers
Torin F. Stetina, Anthony Ciavarella, Xiaosong Li +1
In recent years simulations of chemistry and condensed materials has emerged as one of the preeminent applications of quantum computing, offering an exponential speedup for the sol…