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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.

168,694 papers · 148 categories

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48 results for Adiabatic Quantum Computers

Quantum computing for machine learning attracts increasing attention and recent technological developments suggest that especially adiabatic quantum computing may soon be of practical interest. In this paper, we therefore consider this paradigm and discuss how to adopt it to the problem of binary clustering. Numerical …

2017-06-17abs ↗pdf ↗

This paper uses quantum computing to solve sparse linear regression problems efficiently.

problem Sparse linear regression to identify important features from a large set of variables.
method Formulates the 0\ell_0 optimization problem as a QUBO problem and solves it using the D-Wave adiabatic quantum computer.
result The QUBO solution matches the optimal solution for a wide range of sparsity penalty values across datasets.

Survey on quantum computing and neural networks.

problem Understanding and comparing quantum computing and neural networks.
method Introduction to quantum computing concepts, explanation of quantum computing paradigms, and analysis of quantum neural networks.
result Current state-of-the-art in quantum neural networks.

This paper uses QUBO to train machine learning models on quantum computers.

problem Efficiently training machine learning models on quantum computers.
method Formulated three machine learning models (linear regression, SVM, k-means) as QUBO problems.
result Formulations are more efficient or equivalent in time and space complexity to classical methods.

New method uses adiabatic principles to improve ground-state preparation in quantum computing.

problem Challenges in variational training of complex energy landscapes.
method Iterative Hamiltonian deformation complemented with adiabatic principles.
result Consistent convergence to target ground state through sequence of intermediate problems.

Quantum machine learns faster by reverse annealing on AQCs.

problem Training RBMs on AQCs is hard due to low qubit connectivity.
method Embedding RBM nodes to virtual qubits, semantic quantum search, reverse annealing schedule.
result Reverse annealing accelerates RBM training and improves reconstruction scores.

We study the generating functional, the adiabatic curvature and the adiabatic phase for the integer quantum Hall effect (QHE) on a compact Riemann surface. For the generating functional we derive its asymptotic expansion for the large flux of the magnetic field, i.e., for the large degree kk of the positive Hermitian …

2015-10-22abs ↗pdf ↗

Unified geometric framework for adiabatic quantum mechanics.

problem Understanding geometric phases and exceptional points in quantum mechanics.
method Formal geometric framework for arbitrary non-degenerate Hamiltonians.
result Generalization of geometric phase to non-Hermitian Hamiltonians.

Optimizes trading trajectories for large portfolios quickly.

problem Optimizing trading trajectories for large portfolios with constraints.
method Simulated bifurcation algorithm applied to portfolio optimization.
result First numerical results confirm SB algorithm's power for portfolio optimization.

Tangle machines are a topologically inspired diagrammatic formalism to describe information flow in networks. This paper begins with an expository account of tangle machines motivated by the problem of describing `covariance intersection' fusion of Gaussian estimators in networks. It then gives two examples in which ta…

2015-11-16abs ↗pdf ↗

A key problem in financial mathematics is the forecasting of financial crashes: if we perturb asset prices, will financial institutions fail on a massive scale? This was recently shown to be a computationally intractable (NP-hard) problem. Financial crashes are inherently difficult to predict, even for a regulator whic…

2018-10-16abs ↗pdf ↗

Tangle machines are topologically inspired diagrammatic models. Their novel feature is their natural notion of equivalence. Equivalent tangle machines may differ locally, but globally they are considered to share the same information content. The goal of tangle machine equivalence is to provide a context-independent me…

2014-04-10abs ↗pdf ↗

Quantum-assisted VAE improves similarity search in high-dimensional datasets.

problem Finding fast and memory-efficient similarity search in high-dimensional data.
method Construct a space-efficient search index based on the latent space of a Quantum-assisted Variational Autoencoder (QVAE).
result Real-world speedups and memory-efficient scaling to half a billion data points.

Hybrid QAOA approach optimizes portfolios with strict constraints, outperforming classical methods.

problem Combinatorial optimization under strict cardinality constraints in portfolio management.
method Constraint-preserving QAOA with XY-mixers and Trotterized initialization.
result QAOA achieves a Sharpe Ratio of 1.81, significantly outperforming classical methods.

We apply the geometric-topology surgery theory on spacetime manifolds to study the constraints of quantum statistics data in 2+1 and 3+1 spacetime dimensions. First, we introduce the fusion data for worldline and worldsheet operators capable creating anyon excitations of particles and strings, well-defined in gapped st…

2016-02-18abs ↗pdf ↗

We present a new proof, as well as a C/Q{\bf C/Q} extension, of the Riemann-Roch-Grothendieck theorem of Bismut-Lott for flat vector bundles. The main techniques used are the computations of the adiabatic limits of ηη-invariants associated to the so-called sub-signature operators. We further show that the Bismut-Lott a…

2004-05-31abs ↗pdf ↗

To formulate the universal constraints of quantum statistics data of generic long-range entangled quantum systems, we introduce the geometric-topology surgery theory on spacetime manifolds where quantum systems reside, cutting and gluing the associated quantum amplitudes, specifically in 2+1 and 3+1 spacetime dimension…

2019-01-31abs ↗pdf ↗

Study adiabatic limits of calibrated submanifolds in Riemannian geometry.

problem Understanding the behavior of calibrated submanifolds under adiabatic limits.
method Define a 1-parameter family of forms and study their adiabatic limit, showing it is a generalized calibration.
result Adiabatic calibrated submanifolds are anisotropic minimal in the classical sense.

The gluing formula of the zeta-determinant of a Laplacian given by Burghelea, Friedlander and Kappeler contains an unknown constant. In this paper we compute this constant to complete the formula under the assumption of the product structure near boundary. As applications of this result,we prove the adiabatic decomposi…

2003-04-18abs ↗pdf ↗

We use adiabatic limits to study foliated manifolds. The Bott connection naturally shows up as the adiabatic limit of Levi-Civita connections. As an application, we then construct certain natural elliptic operators associated to the foliation and present a direct geometric proof of a vanshing theorem of Connes[Co], whi…

1999-12-29abs ↗pdf ↗

We obtain an asymptotic formula for the spectrum distribution function of the Laplace operator on a compact Riemannian Sol-manifold in the adiabatic limit determined by a one-dimensional foliation defined by the orbits of a left-invariant flow.

2008-02-09abs ↗pdf ↗

We discuss asymptotic behavior of the eigenvalue distribution of the differential form Laplacian on a Riemannian foliated manifold when the metric on the ambient manifold is blown up in directions normal to the leaves (in the adiabatic limit). Motivated by analogies with semiclassical spectral asymptotics, we use ideas…

2010-06-25abs ↗pdf ↗

We extend the calculus of adiabatic pseudo-differential operators to study the adiabatic limit behavior of the eta and zeta functions of a differential operator δδ, constructed from an elliptic family of operators indexed by S1S^1. We show that the regularized values η(δt,0)η(δ_t,0) and tζ(δt,0)tζ(δ_t,0) are smooth functions of …

2002-04-12abs ↗pdf ↗

Solves a long-standing problem in Kähler geometry.

problem Existence of constant scalar curvature Kähler metrics on projectivized vector bundles.
method Introduces adiabatic slope stability, a weaker version of K-stability, and uses test configurations from subsheaves.
result Equivalence between adiabatic slope stability and existence of cscK metrics for simple vector bundles.

Develops adiabatic theory for ACW flow on surfaces.

problem Evolution of large closed surfaces under area-constrained Willmore flow.
method Constructs a map on a four-dimensional manifold of barycenters to characterize ACW flow dynamics.
result Explicit four-dimensional effective dynamics of barycenters serves as an asymptotic approximation for ACW flow.