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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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4896144192 · May 202619922001200920172026
48 results for geometric quantisation

We study algebro-geometric consequences of the quantised extremal Kähler metrics, introduced in the previous work of the author. We prove that the existence of quantised extremal metrics implies weak relative Chow polystability. As a consequence, we obtain asymptotic weak relative Chow polystability and KK-semistabili…

2017-05-31abs ↗pdf ↗

We provide a Geometric Quantisation formulation of the AJ-conjecture for the Teichmüller TQFT, and we prove it in detail in the case of the knot complements of 414_{1} and 525_2. The conjecture states that the level-NN Andersen-Kashaev invariant, JM,K(b,N)J^{(\mathrm{b},N)}_{M,K}, is annihilated by the non-homogeneous $\hat{…

2017-11-30abs ↗pdf ↗

Survey of bundle gerbes in geometry, field theory, and quantization.

problem Exploring bundle gerbes and their applications in geometry, field theory, and quantization.
method Definition and classification of bundle gerbes with connection, surface holonomy, transgression line bundles, and geometric quantization.
result Bundle gerbes provide a smooth bordism-type field theory and geometric quantization for 2-plectic and symplectic forms.

In quantum physics, the operators associated with the position and the momentum of a particle are unbounded operators and CC^*-algebraic quantisation does therefore not deal with such operators. In the present article, I propose a quantisation of the Lie-Poisson structure of the dual of a Lie algebroid which deals wit…

2004-11-03abs ↗pdf ↗

For spherically symmetric distributions, efficient quantisation can be achieved with moderate sample sizes.

problem Optimal quantisation in high dimensions requires large sample sizes, making it impractical.
method Uniformly distributed random quantisers on a sphere of suitable radius achieve exceptional performance.
result For moderate sample sizes, quantisation error can be efficiently computed and approximated.

These notes give an introduction to Geometric Invariant Theory and symplectic reduction, with lots of pictures and simple examples. We describe their applications to moduli of bundles and varieties, and their infinite dimensional analogues in gauge theory and the theory of special metrics on algebraic varieties. Donald…

2005-12-17abs ↗pdf ↗

Quantized BNNs maintain uncertainty estimation quality despite reduced precision.

problem Reduced precision in BNNs due to quantization.
method Quantized BNNs with 32-bit weights and activations compressed to 16-bit integers.
result Uniform quantization does not significantly degrade uncertainty estimation quality.

We describe in elementary geometrical terms Teichm\" uller spaces of decorated and holed surfaces. We construct explicit global coordinates on them as well as on the spaces of measured laminations with compact and closed support respectively. We show explicitly that the latter spaces are asymptotically isomorphic to th…

1997-02-20abs ↗pdf ↗

Efficiently calibrates Bergomi models to VIX derivatives using vector quantization.

problem Calibrating Bergomi models to VIX derivatives for accurate pricing.
method Applied vector quantization in mixed Bergomi models for fast and efficient option pricing.
result Calibration of Bergomi models to VIX derivatives is feasible and accurate over daily data.

Neural networks help auditors efficiently assess financial statements by learning underlying data patterns.

problem Efficiently auditing large volumes of financial statements and journal entries.
method Vector Quantised-Variational Autoencoder (VQ-VAE) neural networks.
result VQ-VAE neural networks can learn a quantized representation of accounting data, uncovering latent factors and providing a representative audit sample.

Improved hierarchical discrete VAEs for better stability and performance.

problem Training stable and efficient hierarchical discrete VAEs with numerous latent variables.
method Introducing Relaxed-Responsibility Vector-Quantisation to parameterise discrete latent variables in a hierarchical structure.
result Achieved state-of-the-art bits-per-dim results for various standard datasets.

A new algorithm improves Bayesian federated learning by reducing communication overhead.

problem Bayesian federated learning constraints, including privacy, data ownership, and communication overhead.
method Proposes Quantised Langevin Stochastic Dynamics (QLSD) for Bayesian federated learning, using gradient compression and variance reduction techniques.
result Non-asymptotic and asymptotic convergence guarantees for QLSD and its improved versions.

Global analysis of Dixmier traces and Wodzicki residues on compact Lie groups.

problem Computing Dixmier traces and Wodzicki residues on compact Lie groups.
method Global quantisation approach, using global symbols and representation theory.
result Explicit formulae for Dixmier traces and Wodzicki residues on compact Lie groups.

We study noncommutative bundles and Riemannian geometry at the semiclassical level of first order in a deformation parameter λλ, using a functorial approach. The data for quantisation of the cotangent bundle is known to be a Poisson structure and Poisson preconnection and we now show that this data defines to a functo…

2014-03-17abs ↗pdf ↗

Paradan and Vergne generalised the quantisation commutes with reduction principle of Guillemin and Sternberg from symplectic to Spinc^c-manifolds. We extend their result to noncompact groups and manifolds. This leads to a result for cocompact actions, and a result for non-cocompact actions for reduction at zero. The r…

2014-08-01abs ↗pdf ↗

In this paper we explore the idea of looking at the Dirac quantisation conditions as \hbar-dependent constraints on the tangent bundle to phase-space. Starting from the path-integral version of classical mechanics and using the natural Poisson brackets structure present in the cotangent bundle to the tangent bundle o…

1997-03-26abs ↗pdf ↗

We consider a class of time dependent finite energy multi-soliton solutions of the U(N) integrable chiral model in (2+1)(2+1) dimensions. The corresponding extended solutions of the associated linear problem have a pole with arbitrary multiplicity in the complex plane of the spectral parameter. Restrictions of these exten…

2006-05-18abs ↗pdf ↗

Quantizes Maxwell's theory on Lorentzian manifolds via a novel gauge-fixing method.

problem Quantizing Maxwell's theory on Lorentzian manifolds with complete gauge fixing.
method New Hodge decomposition for differential k-forms in Sobolev spaces and pseudodifferential calculus for state construction.
result Existence of Hadamard states for Maxwell's theory.

In the framework of Galilei classical mechanics (i.e., general relativistic classical mechanics on a spacetime with absolute time) developed by Jadczyk and Modugno, we analyse systematically the relations between symmetries of the geometric objects. We show that the (holonomic) infinitesimal symmetries of the cosymplec…

2000-03-24abs ↗pdf ↗

The study examines Kähler structures on coadjoint orbits of Lie groups using coherent and squeezed states.

problem Does the coadjoint orbits of Lie groups support a Kähler structure?
method Examined three Lie groups: Weyl-Heisenberg, SU(2), and SU(1,1). Used coherent and squeezed states to explore Kähler structures.
result Coherent states provide Kähler embeddings, while squeezed states only symplectic embeddings.

The study explores Lorentzian manifolds with specific null vector fields and their geometric properties.

problem Characterizing Lorentzian manifolds with shearfree null vector fields and their quotient structures.
method Analyzing quotient spaces and constructing metrics on total spaces of bundles.
result Existence of non-trivial generalized electromagnetic plane waves and Einstein metrics.

New algorithms minimize MMD to approximate probability measures efficiently.

problem Approximating probability measures by representative point sets.
method Sequential greedy minimization of maximum mean discrepancy (MMD) over candidate sets, with mini-batch variants.
result Consistency of proposed algorithms and mini-batch variants established.

This paper shows connections between two complex mathematical theories are equivalent.

problem Establishing equivalence between two complex mathematical theories.
method Using geometric quantisation and conformal field theory, the paper establishes equivalence between the Hitchin connection and the Knizhnik-Zamolodchikov connection.
result The Hitchin and Knizhnik-Zamolodchikov connections are projectively equivalent in genus zero.

The geometric approach [1312.1262] to iterated variations of local functionals -- e.g., of the (master-)action functional -- resulted in an extension of the deformation quantisation technique to the set-up of Poisson models of field theory [IHES/M/15/13]. It also allowed of a rigorous proof ([1312.1262],[1210.0726]) fo…

2014-10-01abs ↗pdf ↗

The goal of this note is to give a brief overview of the BV-BFV formalism developed by the first two authors and Reshetikhin in [arXiv:1201.0290], [arXiv:1507.01221] in order to perform perturbative quantisation of Lagrangian field theories on manifolds with boundary, and present a special case of Chern-Simons theory a…

2015-12-02abs ↗pdf ↗

Suppose that a polarised Kähler manifold (X,L)(X,L) admits an extremal metric ωω. We prove that there exists a sequence of Kähler metrics {ωk}k\{ ω_k \}_k, converging to ωω as kk \to \infty, each of which satisfies the equation ˉgradωk1,0ρk(ωk)=0\bar{\partial} \text{grad}^{1,0}_{ω_k} ρ_k (ω_k)=0; the (1,0)(1,0)-part of the gradient of the B…

2015-08-11abs ↗pdf ↗

In large scale systems, approximate nearest neighbour search is a crucial algorithm to enable efficient data retrievals. Recently, deep learning-based hashing algorithms have been proposed as a promising paradigm to enable data dependent schemes. Often their efficacy is only demonstrated on data sets with fixed, limite…

2019-02-11abs ↗pdf ↗

Let L be an ample bundle over a compact complex manifold X. Fix a Hermitian metric in L whose curvature defines a Kähler metric on X. The Hessian of Mabuchi energy is a fourth-order elliptic operator D on functions which arises in the study of scalar curvature. We quantise D by the Hessian E(k) of balancing energy, a f…

2010-09-23abs ↗pdf ↗

Modality-agnostic compression improves across diverse data types.

problem Efficiently compressing data across multiple modalities.
method Functional view of data, Implicit Neural Representation (INR), modality-agnostic latent representations, variational compression.
result Improved performance compared to existing methods, especially for diverse modalities.

In the theory of so called "Covariant Quantum Mechanics" a basic role is played by Hermitian vector fields on a complex line bundle in the frameworks of Galilei and Einstein spacetimes. In fact, it has been proved that the Lie algebra of Hermitian vector fields is naturally isomorphic to a Lie algebra of "special funct…

2005-04-15abs ↗pdf ↗

Consider a proper, isometric action by a unimodular, locally compact group GG on a complete Riemannian manifold MM. For equivariant elliptic operators that are invertible outside a cocompact subset of MM, we show that a localised index in the KK-theory of the maximal group CC^*-algebra of GG is well-defined. The …

2019-09-25abs ↗pdf ↗

This thesis proposes a global geometric formulation of Extended Field Theories.

problem Global understanding of Extended Field Theories remains an open problem.
method Introducing an atlas for the principal infinity-bundle, unifying metric and higher gauge field.
result Global abelian T-duality and Poisson-Lie T-duality are automatically recovered.

Projective connections first appeared in Cartan's papers in the 1920's. Since then they have resurfaced periodically in, for example, integrable systems and perhaps most recently in the context of so called projectively equivariant quantisation. We recall the notion of projective connection and describe its relation wi…

2008-08-20abs ↗pdf ↗

We describe the multi-GPU gradient boosting algorithm implemented in the XGBoost library (https://github.com/dmlc/xgboost). Our algorithm allows fast, scalable training on multi-GPU systems with all of the features of the XGBoost library. We employ data compression techniques to minimise the usage of scarce GPU memory …

2018-06-29abs ↗pdf ↗