14 results match your criteria: "Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning[Affiliation]"

Nonadiabatic dynamics is key for understanding solar energy conversion and photochemical processes in condensed phases. This often involves the non-Markovian dynamics of the reduced density matrix in open quantum systems, where knowledge of the system's prior states is necessary to predict its future behavior. In this study, we explore time-series machine learning methods for predicting long-time nonadiabatic dynamics based on short-time input data, comparing these methods with the physics-based transfer tensor method (TTM).

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The rapid progression of machine learning, especially deep learning (DL), has catalyzed a new era in drug discovery, introducing innovative approaches for predicting molecular properties. Despite the many methods available for feature representation, efficiently utilizing rich, high-dimensional information remains a significant challenge. Our work introduces ChemXTree, a novel graph-based model that integrates a Gate Modulation Feature Unit (GMFU) and neural decision tree (NDT) in the output layer to address this challenge.

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Article Synopsis
  • The study explores how errors in estimating stimuli, particularly in visual orientation perception, change during cognitive processes like working memory.
  • It reveals that these evolving errors require interaction between two specific modules: one for sensory encoding and another for memory maintenance, as they can't function efficiently in a single-module network.
  • The sensory module is designed to represent varied orientations dynamically, while the memory module maintains a more uniform representation, showing the importance of sensory-memory interaction in shaping how we perceive stimuli over time.
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Article Synopsis
  • Distinguishing between reality and hallucinations relies on monitoring agency, which may be disrupted by a breakdown in motor signal processes known as efference copy (EC) or corollary discharge (CD).
  • Research using EEG with patients experiencing auditory verbal hallucinations (AVHs) shows that the lack of inhibition typically seen in CD contributes to the emergence of these hallucinations, particularly affecting how sensory responses are managed.
  • The findings indicate that impaired CD and EC functions lead to a misinterpretation of internal auditory signals, causing the positive symptoms observed in hallucinations, particularly in individuals with schizophrenia.
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In this work, we introduce PyCTRAMER, a comprehensive Python package designed for calculating charge transfer (CT) rate constants in disordered condensed-phase systems at finite temperatures, such as organic photovoltaic (OPV) materials. PyCTRAMER is a restructured and enriched version of the CTRAMER (Charge-Transfer RAtes from Molecular dynamics, Electronic structure, and Rate theory) package [Tinnin et al. J.

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HSADab: A comprehensive database for human serum albumin.

Int J Biol Macromol

October 2024

NYU-ECNU Center for Computational Chemistry and Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning, NYU Shanghai, Shanghai 200062, China; Department of Chemistry, New York University, NY NY10003, USA; Faculty of Synthetic Biology and Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. Electronic address:

Human Serum Albumin (HSA), the most abundant protein in human body fluids, plays a crucial role in the transportation, absorption, metabolism, distribution, and excretion of drugs, significantly influencing their therapeutic efficacy. Despite the importance of HSA as a drug target, the available data on its interactions with external agents, such as drug-like molecules and antibodies, are limited, posing challenges for molecular modeling investigations and the development of empirical scoring functions or machine learning predictors for this target. Furthermore, the reported entries in existing databases often contain major inconsistencies due to varied experiments and conditions, raising concerns about data quality.

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We recently introduced a polarizable embedding scheme based on an integral-exact reformulation of the direct reaction field method (IEDRF) that accounts for the differential solvation of ground and excited states in QM/MM simulations. The polarization and dispersion interactions between the quantum-mechanical (QM) and molecular-mechanical (MM) regions are described by the DRF Hamiltonian, while the Pauli repulsion between explicitly treated QM electrons and the implicit electron density around MM atoms is modeled with effective core potentials. A single Hamiltonian is used for all electronic states so that Born-Oppenheimer states belonging to the same geometry are orthogonal and state crossings are well-defined.

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Optical circuit compactification for ultracold atoms.

Rev Sci Instrum

January 2024

State Key Laboratory of Precision Spectroscopy, School of Physical and Material Sciences, East China Normal University, Shanghai 200062, China.

We develop a modular and compactified optical circuit for the generation of optical beams for cooling, imaging, and controlling ultracold atoms. One of the simplifications that is made in our circuit is to admix the repumping beams to each other optical beams in its dedicated single-mode fiber. We implement our design, characterize the output, and show that the optical power efficiency of the circuit is in the region of 97%, and after fiber coupling, the efficiencies are in the range of 62-85%.

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Generalized nonequilibrium Fermi's golden rule and its semiclassical approximations for electronic transitions between multiple states.

J Chem Phys

January 2024

Division of Arts and Sciences, NYU Shanghai, 567 West Yangsi Road, Shanghai 200124, China.

The nonequilibrium Fermi's golden rule (NE-FGR) approach is developed to simulate the electronic transitions between multiple excited states in complex condensed-phase systems described by the recently proposed multi-state harmonic (MSH) model Hamiltonian. The MSH models were constructed to faithfully capture the photoinduced charge transfer dynamics in a prototypical organic photovoltaic carotenoid-porphyrin-C60 molecular triad dissolved in tetrahydrofuran. A general expression of the fully quantum-mechanical NE-FGR rate coefficients for transitions between all pairs of states in the MSH model is obtained.

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Multistate Reaction Coordinate Model for Charge and Energy Transfer Dynamics in the Condensed Phase.

J Chem Theory Comput

October 2023

Division of Arts and Sciences, NYU Shanghai, 567 West Yangsi Road, Shanghai, 200124, China.

Constructing multistate model Hamiltonians from all-atom electronic structure calculations and molecular dynamics simulations is crucial for understanding charge and energy transfer dynamics in complex condensed phases. The most popular two-level system model is the spin-boson Hamiltonian, where the nuclear degrees of freedom are represented as shifted normal modes. Recently, we proposed the general multistate nontrivial extension of the spin-boson model, i.

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Measurement-Based Deterministic Imaginary Time Evolution.

Phys Rev Lett

September 2023

State Key Laboratory of Precision Spectroscopy, School of Physical and Material Sciences, East China Normal University, Shanghai 200062, China.

We introduce a method to perform imaginary time evolution in a controllable quantum system using measurements and conditional unitary operations. By performing a sequence of weak measurements based on the desired Hamiltonian constructed by a Suzuki-Trotter decomposition, an evolution approximating imaginary time evolution can be realized. The randomness due to measurement is corrected using conditional unitary operations, making the evolution deterministic.

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Segregation and integration of sensory features by flexible temporal characteristics of independent neural representations.

Cereb Cortex

August 2023

Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China.

Segregation and integration are two fundamental yet competing computations in cognition. For example, in serial speech processing, stable perception necessitates the sequential establishment of perceptual representations to remove irrelevant features for achieving invariance. Whereas multiple features need to combine to create a coherent percept.

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We present efficient analytical gradients of property-based diabatic states and couplings using a Lagrangian formalism. Unlike previous formulations, the method achieves a computational scaling that is independent of the number of adiabatic states used to construct the diabats. The approach is generalizable to other property-based diabatization schemes and electronic structure methods as long as analytical energy gradients are available and integral derivatives with the property operator can be formed.

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Dual-stream cortical pathways mediate sensory prediction.

Cereb Cortex

July 2023

Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning, Division of Arts and Sciences, New York University Shanghai, Shanghai 200126, China.

Predictions are constantly generated from diverse sources to optimize cognitive functions in the ever-changing environment. However, the neural origin and generation process of top-down induced prediction remain elusive. We hypothesized that motor-based and memory-based predictions are mediated by distinct descending networks from motor and memory systems to the sensory cortices.

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