Results 141 to 150 of about 6,748,421 (282)

Continuous-variable Quantum Phase Estimation based on Machine Learning. [PDF]

Sci Rep, 2019
Xiao T, Huang J, Fan J, Zeng G.
europepmc   +1 more source

Adiabatic Quantum Phase Estimation

6 + 11 pages, 2 ...
Schmidhuber, Alexander, Lloyd, Seth
openaire   +2 more sources

Benchmarking Bayesian quantum estimation [PDF]

The quest for precision in parameter estimation is a fundamental task in different scientific areas. The relevance of this problem thus provided the motivation to develop methods for the application of quantum resources to estimation protocols.
Cimini, Valeria, Sciarrino, Fabio, Spagnolo, Nicolò, Polino, Emanuele, Valeri, Mauro   +4 more
core   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Thermodynamic Limits to Molecular Doping in Conjugated Polymers: A Perspective on Phase Behavior and Miscibility

Advanced Materials, EarlyView.
Molecular doping of conjugated polymers is fundamentally constrained by thermodynamic phase behavior. This Perspective reframes doping efficiency and stability in terms of miscibility limits, binodals, and solvus boundaries, highlighting the role of effective interaction parameters and charge transfer.
Somayeh Kashani, Justin Neu, Sung‐Joo Kwon, Runqio Song, Zixuan Chen, Tajah Trapier, Paschalis Gkoupidenis, David Ginger, Wei You, Jasper J. Michels, Harald Ade   +10 more
wiley   +1 more source

When Poor Exciton Dissociation Limits Photocurrents in Organic Solar Cells: Why Low Offset Non‐Fullerene Acceptor Blends Can't Be Efficient

Advanced Materials, EarlyView.
The energetic offset between the donor and the acceptor components in organic photoactive layers is central to the tradeoff between photovoltage and photocurrent losses. This Perspective covers the most important issues surrounding this topic in non‐fullerene acceptor blends, from the difficulty of accurately determining state energies and driving ...
Dieter Neher, Manasi Pranav
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Optimal multiple-phase estimation with multi-mode NOON states against photon loss

New Journal of Physics
Multi-mode NOON states can quantum-enhance multiple-phase estimation in the absence of photon loss. However, a multi-mode NOON state is known to be vulnerable to photon loss, and its quantum-enhancement can be dissipated by lossy environment.
Min Namkung, Dong-Hyun Kim, Seongjin Hong, Yong-Su Kim, Changhyoup Lee, Hyang-Tag Lim   +5 more
doaj   +1 more source

Why Is the Mechanism Underlying the Chiral‐Induced Selectivity Effect Still Challenging?

Advanced Materials, EarlyView.
The chiral‐induced spin selectivity (CISS) effect is observed in many experimental configurations and for different materials. However, there are theoretical challenges in attempting to explain those results. A qualitative framework for explaining all the results is presented.
Ron Naaman, Yossi Paltiel
wiley   +1 more source

Heisenberg-limited Bayesian phase estimation with low-depth digital quantum circuits

npj Quantum Information
Optimal phase estimation protocols require complex state preparation and readout schemes, generally unavailable or unscalable in many quantum platforms. We develop a scheme that achieves near-optimal precision up to a constant overhead for Bayesian phase
Su Direkci, Ran Finkelstein, Manuel Endres, Tuvia Gefen   +3 more
doaj   +1 more source