What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Artificial intelligence
- Electron
His primary areas of investigation include Quantum, Quantum computer, Quantum mechanics, Statistical physics and Quantum simulator.
His research in Quantum intersects with topics in Hamiltonian, Coherence, Fenna-Matthews-Olson complex and Molecular dynamics.
His Quantum computer research integrates issues from Quantum information, Computational chemistry, Quantum algorithm and Theoretical computer science.
His studies deal with areas such as Simple, Decoding methods and Representation as well as Theoretical computer science.
Alán Aspuru-Guzik interconnects Wave function, Excited state, Coupled cluster, Ground state and Discretization in the investigation of issues within Statistical physics.
While the research belongs to areas of Quantum simulator, Alán Aspuru-Guzik spends his time largely on the problem of Quantum chemistry, intersecting his research to questions surrounding Ion.
His most cited work include:
- Advances in molecular quantum chemistry contained in the Q-Chem 4 program package (1461 citations)
- A variational eigenvalue solver on a photonic quantum processor (1127 citations)
- Convolutional networks on graphs for learning molecular fingerprints (980 citations)
What are the main themes of his work throughout his whole career to date?
Alán Aspuru-Guzik mainly investigates Quantum, Quantum computer, Quantum mechanics, Statistical physics and Quantum algorithm.
He has researched Quantum in several fields, including Hamiltonian and Ground state.
His research integrates issues of Quantum information, Theoretical physics, Wave function and Topology in his study of Quantum computer.
His Open quantum system, Quantum process and Quantum decoherence study are his primary interests in Quantum mechanics.
As part of his studies on Statistical physics, Alán Aspuru-Guzik often connects relevant areas like Quantum Monte Carlo.
His studies in Quantum algorithm integrate themes in fields like Algorithm and Quantum operation.
He most often published in these fields:
- Quantum (25.78%)
- Quantum computer (18.01%)
- Quantum mechanics (14.60%)
What were the highlights of his more recent work (between 2019-2021)?
- Quantum (25.78%)
- Artificial intelligence (9.55%)
- Quantum computer (18.01%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Quantum, Artificial intelligence, Quantum computer, Chemical space and Quantum simulator.
His study in Quantum is interdisciplinary in nature, drawing from both Ground state and Topology.
His Deep learning and Artificial neural network study in the realm of Artificial intelligence connects with subjects such as Chemistry.
The Quantum computer study combines topics in areas such as Quantum information science and Computer engineering.
His Chemical space research includes elements of Virtual screening, Representation, Molecule and Generative grammar, Generative model.
His Quantum simulator study also includes
- Energy functional, Statistical physics and Eigenvalues and eigenvectors most often made with reference to Hamiltonian,
- Superconductivity most often made with reference to Energy.
Between 2019 and 2021, his most popular works were:
- Quantum computational chemistry (250 citations)
- QSAR without borders (83 citations)
- Self-driving laboratory for accelerated discovery of thin-film materials. (57 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Artificial intelligence
- Electron
His primary scientific interests are in Quantum, Quantum computer, Theoretical computer science, Artificial intelligence and Artificial neural network.
His Quantum study often links to related topics such as Topology.
His work in the fields of Quantum machine learning overlaps with other areas such as Key and Probability distribution.
His research in Theoretical computer science focuses on subjects like Representation, which are connected to Virtual screening and Generative grammar.
His work in Artificial intelligence covers topics such as Machine learning which are related to areas like Orders of magnitude and Domain knowledge.
His Artificial neural network study combines topics from a wide range of disciplines, such as Oxidative addition, Message passing and Graph.
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