44,599 research outputs found
Two-hole ground state wavefunction: Non-BCS pairing in a - two-leg ladder system
Superconductivity is usually described in the framework of the
Bardeen-Cooper-Schrieffer (BCS) wavefunction, which even includes the
resonating-valence-bond (RVB) wavefunction proposed for the high-temperature
superconductivity in the cuprate. A natural question is \emph{if} any
fundamental physics could be possibly missed by applying such a scheme to
strongly correlated systems. Here we study the pairing wavefunction of two
holes injected into a Mott insulator/antiferromagnet in a two-leg ladder using
variational Monte Carlo (VMC) approach. By comparing with density matrix
renormalization group (DMRG) calculation, we show that a conventional BCS or
RVB pairing of the doped holes makes qualitatively wrong predictions and is
incompatible with the fundamental pairing force in the - model, which is
kinetic-energy-driven by nature. By contrast, a non-BCS-like wavefunction
incorporating such novel effect will result in a substantially enhanced pairing
strength and improved ground state energy as compared to the DMRG results. We
argue that the non-BCS form of such a new ground state wavefunction is
essential to describe a doped Mott antiferromagnet at finite doping.Comment: 11 pages, 5 figure
Incorporating prior financial domain knowledge into neural networks for implied volatility surface prediction
In this paper we develop a novel neural network model for predicting implied
volatility surface. Prior financial domain knowledge is taken into account. A
new activation function that incorporates volatility smile is proposed, which
is used for the hidden nodes that process the underlying asset price. In
addition, financial conditions, such as the absence of arbitrage, the
boundaries and the asymptotic slope, are embedded into the loss function. This
is one of the very first studies which discuss a methodological framework that
incorporates prior financial domain knowledge into neural network architecture
design and model training. The proposed model outperforms the benchmarked
models with the option data on the S&P 500 index over 20 years. More
importantly, the domain knowledge is satisfied empirically, showing the model
is consistent with the existing financial theories and conditions related to
implied volatility surface.Comment: 8 pages, SIGKDD 202
- …