Search Results - "Sornborger, Andrew"

Learning the quantum algorithm for state overlap by Cincio, Lukasz, Suba, Yi it, Sornborger, Andrew T, Coles, Patrick J

“…Short-depth algorithms are crucial for reducing computational error on near-term quantum computers, for which decoherence and gate infidelity remain important…”
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Absence of Barren Plateaus in Quantum Convolutional Neural Networks by Pesah, Arthur, Cerezo, M., Wang, Samson, Volkoff, Tyler, Sornborger, Andrew T., Coles, Patrick J.

“…Quantum neural networks (QNNs) have generated excitement around the possibility of efficiently analyzing quantum data. But this excitement has been tempered by…”
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Barren Plateaus Preclude Learning Scramblers by Holmes, Zoë, Arrasmith, Andrew, Yan, Bin, Coles, Patrick J., Albrecht, Andreas, Sornborger, Andrew T.

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Barren Plateaus Preclude Learning Scramblers by Holmes, Zoë, Arrasmith, Andrew, Yan, Bin, Coles, Patrick J, Albrecht, Andreas, Sornborger, Andrew T

“…Scrambling processes, which rapidly spread entanglement through many-body quantum systems, are difficult to investigate using standard techniques, but are…”
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Variational consistent histories as a hybrid algorithm for quantum foundations by Arrasmith, Andrew, Cincio, Lukasz, Sornborger, Andrew T., Zurek, Wojciech H., Coles, Patrick J.

“…Although quantum computers are predicted to have many commercial applications, less attention has been given to their potential for resolving foundational…”
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Generalization in quantum machine learning from few training data by Caro, Matthias C., Huang, Hsin-Yuan, Cerezo, M., Sharma, Kunal, Sornborger, Andrew, Cincio, Lukasz, Coles, Patrick J.

“…Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making…”
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Graded, Dynamically Routable Information Processing with Synfire-Gated Synfire Chains by Wang, Zhuo, Sornborger, Andrew T, Tao, Louis

“…Coherent neural spiking and local field potentials are believed to be signatures of the binding and transfer of information in the brain. Coherent activity has…”
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Variational fast forwarding for quantum simulation beyond the coherence time by Cîrstoiu, Cristina, Holmes, Zoë, Iosue, Joseph, Cincio, Lukasz, Coles, Patrick J., Sornborger, Andrew

“…Trotterization-based, iterative approaches to quantum simulation (QS) are restricted to simulation times less than the coherence time of the quantum computer…”
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Inference-Based Quantum Sensing by Huerta Alderete, C., Gordon, Max Hunter, Sauvage, Frédéric, Sone, Akira, Sornborger, Andrew T., Coles, Patrick J., Cerezo, M.

“…In a standard quantum sensing (QS) task one aims at estimating an unknown parameter θ, encoded into an n-qubit probe state, via measurements of the system. The…”
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Reformulation of the No-Free-Lunch Theorem for Entangled Datasets by Sharma, Kunal, Cerezo, M, Holmes, Zoë, Cincio, Lukasz, Sornborger, Andrew, Coles, Patrick J

“…The no-free-lunch (NFL) theorem is a celebrated result in learning theory that limits one's ability to learn a function with a training dataset. With the…”
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Out-of-distribution generalization for learning quantum dynamics by Caro, Matthias C., Huang, Hsin-Yuan, Ezzell, Nicholas, Gibbs, Joe, Sornborger, Andrew T., Cincio, Lukasz, Coles, Patrick J., Holmes, Zoë

“…Generalization bounds are a critical tool to assess the training data requirements of Quantum Machine Learning (QML). Recent work has established guarantees…”
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The backpropagation algorithm implemented on spiking neuromorphic hardware by Renner, Alpha, Sheldon, Forrest, Zlotnik, Anatoly, Tao, Louis, Sornborger, Andrew

“…The capabilities of natural neural systems have inspired both new generations of machine learning algorithms as well as neuromorphic, very large-scale…”
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Mutual Information and Information Gating in Synfire Chains by Xiao, Zhuocheng, Wang, Binxu, Sornborger, Andrew, Tao, Louis

“…Coherent neuronal activity is believed to underlie the transfer and processing of information in the brain. Coherent activity in the form of synchronous firing…”
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Quantum Simulation of Tunneling in Small Systems by Sornborger, Andrew T.

“…A number of quantum algorithms have been performed on small quantum computers; these include Shor's prime factorization algorithm, error correction, Grover's…”
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Universal Compiling and (No-)Free-Lunch Theorems for Continuous-Variable Quantum Learning by Volkoff, Tyler, Holmes, Zoë, Sornborger, Andrew

“…Quantum compiling, where a parameterized quantum circuit is trained to learn a target unitary, is an important primitive for quantum computing that can be used…”
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A mechanism for graded, dynamically routable current propagation in pulse-gated synfire chains and implications for information coding by Sornborger, Andrew T., Wang, Zhuo, Tao, Louis

“…Neural oscillations can enhance feature recognition (Azouz and Gray Proceedings of the National Academy of Sciences of the United States of America , 97 ,…”
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Quantum-assisted quantum compiling by Khatri, Sumeet, LaRose, Ryan, Poremba, Alexander, Cincio, Lukasz, Sornborger, Andrew T., Coles, Patrick J.

“…Compiling quantum algorithms for near-term quantum computers (accounting for connectivity and native gate alphabets) is a major challenge that has received…”
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Long-time simulations for fixed input states on quantum hardware by Gibbs, Joe, Gili, Kaitlin, Holmes, Zoë, Commeau, Benjamin, Arrasmith, Andrew, Cincio, Lukasz, Coles, Patrick J., Sornborger, Andrew

“…Publicly accessible quantum computers open the exciting possibility of experimental dynamical quantum simulations. While rapidly improving, current devices…”
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Toward prethreshold gate-based quantum simulation of chemical dynamics: using potential energy surfaces to simulate few-channel molecular collisions by Sornborger, Andrew T., Stancil, Phillip, Geller, Michael R.

“…One of the most promising applications of an error-corrected universal quantum computer is the efficient simulation of complex quantum systems such as large…”
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Binary operations on neuromorphic hardware with application to linear algebraic operations and stochastic equations by Iaroshenko, Oleksandr, Sornborger, Andrew T, Chavez Arana, Diego

“…Abstract Non-von Neumann computational hardware, based on neuron-inspired, non-linear elements connected via linear, weighted synapses—so-called neuromorphic…”
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