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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.

169,291 papers · 148 categories

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18365472 · May 202619922001200920182026
48 results for quantum chain

Quantum algorithms for financial derivatives and credit risk.

problem Estimating credit risk and option pricing in realistic financial models.
method Developed a regime switching volatility model for financial markets, using a Markov chain to determine volatility parameters.
result Quantum algorithms can be applied to realistic financial models, bringing quantum computing closer to practical applications.

The paper calculates the asymptotics of quantum invariants for Whitehead chains.

problem Quantum invariants of Whitehead chains with colored clasps.
method Asymptotic analysis of colored Jones polynomials, considering limiting ratios of sequences.
result The exponential growth rate of invariants matches the hyperbolic volume of link complements.

New approach connects quantum phases to VQA trainability, enabling better scaling.

problem Scalability issues in VQAs, especially barren plateaus.
method Analog VQA ansätze composed of quenches of a disordered Ising chain, tuning disorder strength.
result Thermalized and MBL phases reach maximal expressivity at large MM, but barren plateaus emerge at smaller MM in the thermalized phase.

We prove Tsygan's formality conjecture for Hochschild chains of the algebra of functions on an arbitrary smooth manifold M using the Fedosov resolutions proposed in math.QA/0307212 and the formality quasi-isomorphism for Hochschild chains of R[[y_1, ..., y_d]] proposed in paper math.QA/0010321 by Shoikhet. This result …

2004-02-16abs ↗pdf ↗

The Jones-Wenzl projectors play a central role in quantum topology, underlying the construction of SU(2) topological quantum field theories and quantum spin networks. We construct chain complexes whose graded Euler characteristic is the "classical" projector in the Temperley-Lieb algebra. We show that they are homotopy…

2010-05-27abs ↗pdf ↗

Quantum hardware accelerates training of Boltzmann machines, improving sampling and learning.

problem Training fully visible Boltzmann machines with high-energy barriers.
method Benchmarked quantum annealing hardware for training Boltzmann machines, comparing quantum and classical distributions.
result Quantum hardware can improve training of Boltzmann machines, especially for hard problems.

Quantizes the relationship between Koszul and Schouten brackets in Poisson geometry.

problem Quantizing the relationship between Koszul and Schouten brackets in Poisson geometry.
method Employing Voronov's thick morphism technique and quantum Mackenzie-Xu transformations in the framework of LL_\infty-algebroids.
result Quantizes the LL_\infty-morphism into a single linear operator, a formal Fourier integral operator.

Paper develops security model and pricing for stable digital currency in quantum blockchain network.

problem Securing and pricing stable digital currency in a quantum blockchain network.
method Developed a block-based quantum channel networking technology and a FinTech platform model with dynamic pricing.
result Established a generalized IoB security model using quantum channel networking and QKD.

We prove that Morrison and Nieh's categorification of the su(3) quantum knot invariant is functorial with respect to tangle cobordisms. This is in contrast to the categorified su(2) theory, which was not functorial as originally defined. We use methods of Bar-Natan to construct explicit chain maps for each variation of…

2008-06-03abs ↗pdf ↗

Quantum machine learning classification depends on mutual informations between state and parameter spaces.

problem Generalization in quantum machine learning models.
method Link between quantum machine learning and quantum hypothesis testing, using mutual informations.
result Quantum classifier accuracy and generalization depend on mutual informations between state and parameter spaces.

Quantum annealer speeds up RBM training for image classification.

problem Training RBM with contrastive divergence (CD) is slow and computationally expensive.
method Used D-Wave 2000Q quantum annealer to calculate model expectation of gradient learning for RBM.
result Quantum training yields similar classification performance to CD but faster.

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.

The Temperley-Lieb algebra is a fundamental component of SU(2) topological quantum field theories. We construct chain complexes corresponding to minimal idempotents in the Temperley-Lieb algebra. Our results apply to the framework which determines Khovanov homology. Consequences of our work include semi-orthogonal deco…

2012-09-05abs ↗pdf ↗

We summarize our axioms for higher categories, and describe the blob complex. Fixing an n-category C, the blob complex associates a chain complex B_*(W;C)$ to any n-manifold W. The 0-th homology of this chain complex recovers the usual topological quantum field theory invariants of W. The higher homology groups should …

2011-08-26abs ↗pdf ↗

Deep learning wave function improves quantum chemistry calculations.

problem Solving the electronic Schrödinger equation for complex molecules is computationally expensive.
method PauliNet, a deep learning wave function ansatz that incorporates physics and is trained with VMC.
result PauliNet achieves nearly exact solutions and outperforms other methods for various molecules.

New MCMC method speeds up quantum physics simulations by a factor of 100.

problem Simulating quantum many-body systems with high computational complexity.
method FFT-accelerated MCMC with coupled particle and auxiliary variables.
result Achieves O(NlogN)O(N \log N) scaling, significantly faster than traditional O(N3)O(N^3) methods.

The data of a "2D field theory with a closed string compactification" is an equivariant chain level action of a cell decomposition of the union of all moduli spaces of punctured Riemann surfaces with each component compactified as a pseudomanifold with boundary. The axioms on the data are contained in the following ass…

2007-10-22abs ↗pdf ↗

The paper explores exotic symplectomorphisms and quantum cohomology relations in Fano 3-folds.

problem Existence of exotic symplectomorphisms in Fano 3-folds.
method Construction of AA_\infty-structures, Massey products, Andreadakis-Johnson theory, and analysis of quantum cohomology.
result Existence of exotic symplectomorphisms ψYψ_Y for certain Fano 3-folds.

D-Wave quantum annealing fails to improve sampling quality from RBMs compared to Gibbs sampling.

problem Improving sampling quality from RBMs using D-Wave quantum annealing.
method Comparison of D-Wave quantum annealing and Gibbs sampling for RBM sampling.
result D-Wave sampling does not significantly improve the number of local valleys compared to Gibbs sampling.

HR-calculus enables adaptive processing of quaternion signals.

problem Lack of adaptive processing techniques for quaternion-valued signals.
method Introduction and development of HR-calculus for quaternion algebra.
result Derivation of gradient operator, chain and product derivative rules, and Taylor series expansion for quaternion calculus.