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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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48 results for quantum spectra

This research connects quantum spectra of flag bundles to prime factorization of integers.

problem Understanding the quantum spectra of flag bundles and their relation to prime numbers.
method Functorial and inductive properties of vertical quantum cohomology, relating to analytic number theory.
result The degeneracy of the small vertical quantum spectrum of a Grassmann bundle is controlled by the prime factorization of ranks.

We recently discovered a relationship between the volume density spectrum and the determinant density spectrum for infinite sequences of hyperbolic knots. Here, we extend this study to new quantum density spectra associated to quantum invariants, such as Jones polynomials, Kashaev invariants and knot homology. We also …

2015-06-18abs ↗pdf ↗

We prove that the spectrum constructed by González-Meneses, Manchón and the second author is stably homotopy equivalent to the Khovanov spectrum of Lipshitz and Sarkar at its extreme quantum grading.

2018-03-16abs ↗pdf ↗

Machine learning models simulate molecular spectra and reactions in solvents.

problem Accurate simulation of molecular spectra and reactions in solvent environments.
method Introduced FieldSchNet, a deep neural network for modeling molecular interactions with external fields.
result Demonstrated significant lowering of Claisen rearrangement reaction activation barrier using FieldSchNet.

New stable homotopy refinement of quantum annular Khovanov homology.

problem Quantum topological Hochschild homology and annular Khovanov spectra.
method Introducing quantum topological Hochschild homology (qTHH) and constructing a new stable homotopy refinement of quantum annular Khovanov homology.
result The new stable homotopy refinement agrees with qTHH of spectral Chen-Khovanov tangle bimodules and recovers earlier work.

Quantum models can approximate any function if data encoding allows for a rich enough frequency spectrum.

problem Theoretical properties of quantum machine learning models, particularly their expressive power.
method Investigated how data encoding affects the expressive power of parametrized quantum circuits.
result Quantum models can access increasingly rich frequency spectra by repeating data encoding gates, potentially making them universal function approximators.

New method combines deep learning and quantum mechanics for efficient molecular statistics.

problem Computational expense in extracting statistics from molecular systems.
method Adaptive Markov chain Monte Carlo with Normalizing Flow and MLP for quantum accuracy.
result Rapid convergence to Boltzmann distribution and accurate thermodynamic observables.

Machine learning speeds up quantum chemical calculations of excited states.

problem Accurate quantum chemical calculations of excited states are computationally expensive.
method Employing machine learning to speed up and advance excited-state simulations in various fields.
result Machine learning techniques can significantly reduce computational time for excited-state simulations.

This study connects financial volatility to quantum mechanics on hyperbolic manifolds.

problem Deriving a geometric interpretation of financial volatility.
method Mapping financial pricing to quantum Hamiltonians via transformations.
result Financial volatility is a diffusion process on a hyperbolic manifold.

QNA uses quantum-inspired density operators to diagnose market dependence and structural risk.

problem Lack of unified operator representation for market dependence and structural risk diagnostics.
method Quantum Network of Assets (QNA) framework using density operators.
result QNA entropy remains strongly related to covariance spectral entropy but becomes distinct with multi-feature rolling trajectories.

Study of spectral properties of Lorentzian quasi-Fuchsian manifolds.

problem Understanding the spectral properties of Lorentzian quasi-Fuchsian manifolds.
method Analyzing the geodesic flow, Ruelle resonances, and pseudo-Riemannian Laplacian.
result Meromorphic extension of the resolvent of the pseudo-Riemannian Laplacian with poles of finite rank.

Paper explores ML for UV spectra, showing transferability in chemical space.

problem Modeling excited states and predicting properties of unseen molecules.
method Adapting charge model for excited states, using SchNarc approach.
result ML models can predict properties of unseen molecules and different excited states.

We give a simple sufficient condition for Quinn's "bordism-type spectra" to be weakly equivalent to strictly associative ring spectra. We also show that Poincare bordism and symmetric L-theory are naturally weakly equivalent to monoidal functors. Part of the proof of these statements involves showing that Quinn's funct…

2009-07-14abs ↗pdf ↗

Tomova, along with results of Bachman and Schleimer, showed that any high distance knot has a stair-step bridge spectrum. In this paper, we compute the bridge spectra and distance of generalized Montesinos knots. In particular, we produce the first example of a class of knots which attain the stair-step bridge spectra …

2015-10-28abs ↗pdf ↗

FSPA bypasses eigenvalue estimation for quantum PCA, achieving optimal complexity and robustness.

problem Quantum PCA eigenvalue estimation is computationally expensive and prone to errors.
method Filtered Spectral Projection Algorithm (FSPA) that projects onto the dominant spectral subspace directly.
result FSPA achieves optimal complexity and robustness, outperforming classical methods.

New ICA method for sources with mixed spectra.

problem Inaccurate separation of sources with temporal autocorrelations and mixed spectra.
method Estimates spectral density functions and line spectra using cubic splines and indicator functions, then maximizes the Whittle likelihood function.
result Outperforms existing ICA methods in simulations and EEG data applications.

Jones-Wenzl projectors lifted to Khovanov spectra, proving knot conjectures.

problem Understanding Jones-Wenzl projectors in Khovanov spectra.
method Constructing and studying lifted projectors via maps and polynomial actions.
result Complete computation of 3-colored Khovanov spectrum of the unknot, proving conjectures.

We give a method to calculate spectra of the square of the Rarita-Schwinger operator on compact symmetric spaces. According to Weitzenböck formulas, the operator can be written by the Laplace operator, which is the Casimir operator on compact symmetric spaces. Then we can obtain the spectra by using the Freudenthal's f…

2020-01-17abs ↗pdf ↗

We introduce a framework, twisted parametrized stable homotopy theory, for describing semi-infinite homotopy types. A twisted parametrized spectrum is a section of a bundle whose fibre is the category of spectra. We define these bundles in terms of modules over a stack of parametrized spectra and in terms of diagrams o…

2005-08-03abs ↗pdf ↗

We prove explicit upper and lower bounds for the L1L^1-moment spectra for the Brownian motion exit time from extrinsic metric balls of submanifolds PmP^m in ambient Riemannian spaces NnN^{n}. We assume that PP and NN both have controlled radial curvatures (mean curvature and sectional curvature, respectively) as view…

2010-09-07abs ↗pdf ↗

The paper describes correlations of spectra for higher rank Anosov representations.

problem Understanding correlations of spectra for Anosov representations of higher rank groups.
method Relates correlation problem to counting projections in truncated hypertubes.
result Extends previous work on rank one representations to higher rank.

We view strict ring spectra as generalized rings. The study of their algebraic K-theory is motivated by its applications to the automorphism groups of compact manifolds. Partial calculations of algebraic K-theory for the sphere spectrum are available at regular primes, but we seek more conceptual answers in terms of lo…

2014-03-24abs ↗pdf ↗

By developing a generalized cobordism theory, we explore the higher global symmetries and higher anomalies of quantum field theories and interacting fermionic/bosonic systems in condensed matter. Our essential math input is a generalization of Thom-Madsen-Tillmann spectra, Adams spectral sequence, and Freed-Hopkins's t…

2018-12-31abs ↗pdf ↗

Wavelet scattering spectra model non-Gaussian time-series, proving scale invariance for self-similar processes.

problem Modeling non-Gaussian time-series with stationary increments.
method Complex wavelet transform for scale variations, joint correlation matrix for scale dependencies, second wavelet transform for diagonalization, maximum entropy models conditioned by scattering spectra coefficients.
result Scattering spectra of self-similar processes are scale invariant, allowing statistical testing and generation of new time-series.