Research
On-device research index

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.

168,742 papers · 148 categories

Trend · papers per month

4794141188 · Jun 202019922001200920172026
48 results for quantum behavior

Deeper quantum circuits can improve performance on unseen data, contrary to traditional views.

problem Understanding scaling behavior of parameterized quantum circuits and their generalization.
method Gradient-based PQCs, add-one-in perturbation techniques, spectral properties of random matrices.
result Gradient-based PQCs can exhibit improved performance on unseen data as model size increases, displaying double descent behavior.

Study shows quantum behavior near infinity in metric asymptotics.

problem Quantum behavior of metrics near infinity on quasi-projective manifolds.
method Analysis of Bergman kernel function near smooth divisor at infinity of Cheng-Yau metric.
result Quantum phenomenon observed for points very close to the divisor at infinity.

Quantum circuits predict volatility dynamics preserving asymmetry.

problem Modeling volatility time series with asymmetry.
method Single-qubit quantum circuit learning (QCL) applied to synthetic data generated by Rational GARCH model.
result QCL-based predictions preserve negative return-volatility correlation and anti-persistent behavior.

We pursue the quantum-mechanical challenge to the efficient market hypothesis for the stock market by employing the quantum Brownian motion model. We utilize the quantum Caldeira-Leggett master equation as a possible phenomenological model for the stock-market-prices fluctuations while introducing the external harmonic…

2018-12-01abs ↗pdf ↗

Study explores quantum spaces on toric varieties and their limiting behavior.

problem Understanding quantum spaces on toric varieties and their limiting behavior.
method Established quantum spaces for mixed polarizations and examined one-parameter families of Kähler polarizations.
result Quantum spaces Hk,t\mathcal{H}_{k,t} converge to Hk\mathcal{H}_{k} as tightarrowt ightarrow \infty.

Study shows quantum modularity in figure-eight knot's colored Jones polynomial.

problem Asymptotic behavior of colored Jones polynomial of figure-eight knot.
method Analyzing polynomial evaluated at specific points and showing asymptotic equivalence.
result Quantum modularity demonstrated in the figure-eight knot's colored Jones polynomial.

We construct a new type of quantum walks on simplicial complexes as a natural extension of the well-known Szegedy walk on graphs. One can numerically observe that our proposing quantum walks possess linear spreading and localization as in the case of the Grover walk on lattices. Moreover, our numerical simulation sugge…

2015-07-05abs ↗pdf ↗

A surprising image of the stock market arises if the price time series of all Dow Jones Industrial Average stock components are represented in one chart at once. The chart evolves into a braid representation of the stock market by taking into account only the crossing of stocks and fixing a convention defining overcros…

2014-06-13abs ↗pdf ↗

Econophysics has developed as a research field that applies the formalism of Statistical Mechanics and Quantum Mechanics to address Economics and Finance problems. The branch of Econophysics that applies of Quantum Theory to Economics and Finance is called Quantum Econophysics. In Finance, Quantum Econophysics' contrib…

2015-08-26abs ↗pdf ↗

Proposes a new model to price options considering market forces beyond Black-Scholes.

problem Tackles the limitations of the Black-Scholes model in capturing unexpected market behaviors.
method Uses the analogy between quantum harmonic oscillator and financial market dynamics to propose a new market force-driven model.
result Shows how various market forces can be incorporated to modify option pricing, providing practical applications.

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.

It is believed by the majority today that the efficient market hypothesis is imperfect because of market irrationality. Using the physical concepts and mathematical structures of quantum mechanics, we construct an econophysics framework for the stock market, based on which we analogously map massive numbers of single s…

2014-05-13abs ↗pdf ↗

We present the quantum model of Bertrand duopoly and study the entanglement behavior on the profit functions of the firms. Using the concept of optimal response of each firm to the price of the opponent, we found only one Nash equilibirum point for maximally entangled initial state. The very presence of quantum entangl…

2010-01-16abs ↗pdf ↗
Quantum Econophysicsphysics.soc-ph

The relationships between game theory and quantum mechanics let us propose certain quantization relationships through which we could describe and understand not only quantum but also classical, evolutionary and the biological systems that were described before through the replicator dynamics. Quantum mechanics could be…

2006-09-28abs ↗pdf ↗

Analyzes dynamics of quantum neural networks, predicting exponential decay of training error.

problem Understanding convergence rate of quantum neural networks training.
method Analytic theory for gradient descent dynamics of wide quantum neural networks.
result Simple analytic formula predicts exponential decay of training error.

This work introduces a new quantum kernel, quantum tangent kernel, for improved performance.

problem Improving quantum machine learning performance beyond conventional methods.
method Developed a deep parameterized quantum circuit and used first-order expansion for training.
result The quantum tangent kernel outperforms conventional quantum kernel methods for ansatz-generated datasets.

QNNs can't distinguish binary signals from their negations, revealing a new symmetry.

problem Understanding the behavior of QNNs in binary pattern classification.
method Presented and analyzed a new form of invariance (negational symmetry) in QNNs.
result QNNs cannot differentiate a quantum binary signal and its negational counterpart in binary classification tasks.

A new polynomial invariant for links in a thickened torus exhibits volume conjecture behavior.

problem Defining and characterizing a new polynomial invariant for links in a thickened torus.
method Defining a new invariant JnTJ_n^T, proving properties, and providing constructions.
result The invariant JnTJ_n^T exhibits volume conjecture behavior, providing the first example of this in a virtual link.

Novel framework explains generalization in deep neural networks.

problem Understanding and improving generalization in deep neural networks.
method Topological Quantum Neural Networks as the semi-classical limit of Deep Neural Networks.
result Demonstrates that the perceptron, viewed as the semi-classical limit, achieves similar results to standard neural networks without training.

Quantum models generalize well with little data, challenging traditional generalization theories.

problem Quantum machine learning models generalize well with few data, contradicting traditional theories.
method Systematic randomization experiments and theoretical constructions.
result Quantum neural networks can fit random states and labels, defying current generalization measures.

In this paper, we give a precise and workable definition of a quantum knot system, the states of which are called quantum knots. This definition can be viewed as a blueprint for the construction of an actual physical quantum system. Moreover, this definition of a quantum knot system is intended to represent the "quantu…

2008-05-03abs ↗pdf ↗

Modern approaches to stock pricing in quantitative finance are typically founded on the 'Black-Scholes model' and the underlying 'random walk hypothesis'. Empirical data indicate that this hypothesis works well in stable situations but, in abrupt transitions such as during an economical crisis, the random walk model fa…

2011-10-24abs ↗pdf ↗

Physicists use quantum models to describe the behavior of physical systems. Quantum models owe their success to their interpretability, to their relation to probabilistic models (quantization of classical models) and to their high predictive power. Beyond physics, these properties are valuable in general data science. …

2016-01-22abs ↗pdf ↗

Study on quantum invariants from surgeries on torus knots.

problem Quantum invariants of three-manifolds from surgeries along torus knots.
method Analysis of Witten-Reshetikhin-Turaev invariant and Chern-Simons invariants.
result Quantum invariants can be described as sums of Chern-Simons invariants and twisted Reidemeister torsions.

Quantum computing improves feature selection in machine learning.

problem Optimizing feature selection in machine learning problems.
method Formulated feature selection as a QUBO problem and compared quantum and classical methods.
result Quantum computing can outperform classical methods in feature selection, depending on data set.

This paper applies quantum probability theory to model asset returns, avoiding assumptions about quantum effects.

problem Modeling asset returns with classical probability theory.
method Derives a Schrödinger-like trading equation using quantum probability, linking it to traders' decisions and market behaviors.
result Quantum probability can describe multimodal distributions of asset returns without assuming quantum effects.

New PAC-Bayesian bounds improve understanding of quantum machine learning generalization.

problem Lack of data-dependent, non-uniform generalization bounds for quantum models.
method Derive PAC-Bayesian generalization bounds for quantum models using channel perturbation analysis.
result First non-uniform, data-dependent generalization bounds for quantum models.

The paper connects quantum 6j6j-symbols to tetrahedra volumes via discrete Fourier transforms.

problem Understanding the asymptotic behavior of quantum 6j6j-symbols and their relation to 3-manifold invariants.
method Proposing and proving a conjecture linking discrete Fourier transforms of quantum 6j6j-symbols to the volumes of deeply truncated tetrahedra.
result Supporting evidence for the conjecture in specific cases, with numerical calculations for larger dihedral angles.

We develop a theory of securities price formation and dynamics based on quantum approach and without presuming any similarities with quantum mechanics. Disorder introduced by trading environment leads to probability distribution of returns that is not a smooth curve, but a speckle-pattern fluctuating in both price coor…

2016-04-12abs ↗pdf ↗

Quantum Process Tomography (QPT) methods aim at identifying, i.e. estimating, a given quantum process. QPT is a major quantum information processing tool, since it especially allows one to characterize the actual behavior of quantum gates, which are the building blocks of quantum computers. However, usual QPT procedure…

2019-09-18abs ↗pdf ↗

This paper compares classical shadows and direct quantum measurement for efficient information extraction.

problem Efficiently extracting classical information from quantum states with limited classical post-processing.
method Quantitative resource analysis comparing classical shadows and direct quantum measurement.
result An efficiency frontier between classical shadows and direct quantum measurement is identified.

By analyzing the relationships between a socioeconomical system modeled through evolutionary game theory and a physical system modeled through quantum mechanics we show how although both systems are described through two theories apparently different both are analogous and thus exactly equivalents. The extensions of qu…

2007-04-30abs ↗pdf ↗

Quantum theory explains price dynamics in financial markets, capturing bid-ask spread and ergodicity.

problem Nature of price formation in financial markets and bid-ask spread dynamics.
method Developed a quantum coupled-wave theory using a 2x2 price operator with eigenvalues representing bid and ask prices.
result The theory adequately models bid-ask spread and directional price movement due to quantum-chaotic interaction.