The influence of additional information on the decision making of agents, who are interacting members of a society, is analyzed within the mathematical framework based on the use of quantum probabilities. The introduction of social interactions, which influence the decisions of individual agents, leads to a generalizat…
Quantum framework explains human choices in ambiguity and risk.
problem Testing human choices in ambiguity and risk.
method Quantum-theoretic framework for decision-making under uncertainty.
result Quantum framework faithfully models human choices in ambiguity and risk.
Math connects quantum physics and decision-making.
problem Connecting quantum physics and decision-making models.
method Holonomy concept linking information theory and gauge theories.
result Open questions in both fields.
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…
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.
We investigate how the choice of decision makers can be varied under the presence of risk and uncertainty. Our analysis is based on the approach we have previously applied to individual decision makers, which we now generalize to the case of decision makers that are members of a society. The approach employs the mathem…
Quantum mechanics models human perception and decision-making, offering a new approach to understanding social dynamics.
problem Understanding the complex interactions between individuals and groups in social networks.
method Developed a simple computational code based on quantum mechanics principles to model human perception and decision-making.
result Quantum-inspired models can help explain differences in individual and group behavior.
Quantum approach models economic decisions with probabilistic and dynamic probabilities.
problem Traditional economic models fail to explain recent financial crises.
method Develops a quantum probabilistic framework for economics.
result Quantum circuits can model cognitive phenomena like preference reversal.
Quantum computing speeds up asset pricing models exponentially.
problem Solving dynamic nonlinear asset pricing models efficiently.
method Utilizes quantum superposition and entanglement to solve models exponentially faster than classical methods.
result Exponential computational speed-up for solving asset pricing models.
Quantum circuits represent binary classification trees with binary features.
problem Classifying data using binary classification trees with binary features.
method Quantum circuits and probabilistic approach for traversing decision trees.
result First realization of a decision tree classifier on a quantum device.
Paper tackles interpretability issues in deep learning models.
problem Lack of understanding of deep learning models' decision-making processes.
method Integrates concepts from machine learning, quantum computation, and quantum field theory.
result Demonstrates a many valued quantum logic system in Convolutional Deep Belief Networks.
Quantum version of C5.0 algorithm improves decision tree construction time.
problem Improving the efficiency of decision tree construction in machine learning.
method Improved classical algorithm and applied quantum subroutines for faster decision tree construction.
result Quantum algorithm reduces decision tree construction time significantly.
A new constructivist approach to modeling in economics and theory of consciousness is proposed. The state of elementary object is defined as a set of its measurable consumer properties. A proprietor's refusal or consent for the offered transaction is considered as a result of elementary economic measurement. We were al…
The applications of techniques from statistical (and classical) mechanics to model interesting problems in economics and finance has produced valuable results. The principal movement which has steered this research direction is known under the name of `econophysics'. In this paper, we illustrate and advance some of the…
Quantum algorithms improve reinforcement learning policies.
problem Optimizing decision-making in environments with unknown dynamics.
method Combining quantum value iteration with quantum mean estimation and maximum finding.
result Improved query complexities for computing optimal policies.
End-to-end portfolio optimization using quantum annealing for financial decision problems.
problem Optimizing financial portfolios with quantum computing constraints.
method Hybrid pipeline combining quantum and classical optimization.
result Quantum-assisted portfolio optimization can achieve competitive returns.
Functional integrals explain quantum mechanics and field theory.
problem Explaining quantum mechanics and field theory using functional integrals.
method Describes Feynman's path integral approach to quantum mechanics and field theory.
result Equivalence of path integral formalism to classical mechanics and quantum mechanics.
Novel quantum algorithm for financial market modeling.
problem Accurate quantum state preparation for financial simulation.
method Multi-Split-Steps Quantum Walk (multi-SSQW) with PQC and variational solver.
result Highly accurate modeling of complex financial distributions.
Quantum trace map connects Teichmüller theory and quantum groups.
problem Connecting quantum groups to Teichmüller theory for knots.
method Quantum snakes technology to relate Fock-Goncharov monodromy matrices to quantum SL_n.
result Quantized Fock-Goncharov matrices satisfy quantum SL_n relations.
Quantum theory improves counting overlapping clusters.
problem Counting overlapping clusters in machine learning.
method Applied quantum theory using path integral technique.
result Quantum theory provides a robust statistical method for counting clusters.
Knot theory applied to quantum computing models.
problem Using knot theory for quantum computing models.
method Exploring knot theory applications in quantum computing.
result Knot theory introduces topological concepts to quantum computing.
Projective simulation converges to optimal behavior in Markov decision processes.
problem Optimizing reinforcement learning in Markov decision processes.
method Projective simulation framework applied to reinforcement learning.
result Projective simulation converges to optimal behavior in a large class of Markov decision processes.
Cone structures in quantum field theory linked to information geometry.
problem Understanding geometric structures in quantum field theory.
method Analyzing invariant cones under modular automorphism groups and their relation to Wishart laws.
result Explicit connection between CAH cones and Wishart laws.
Quantum field theory uses Lorentzian bordisms to describe time evolution.
problem Describing the time evolution of quantum field theories.
method Defines a functorial field theory on Lorentzian bordism pseudo-category.
result Lorentzian bordisms naturally arise in algebraic quantum field theory.
Examines quantum mechanics equivalence with Newtonian geometry.
problem Equivalence principle in quantum mechanics.
method Newton--Cartan geometry, non--relativistic twistor theory.
result Discusses equivalence in quantum mechanics.
The Allais and Ellsberg paradoxes show that the expected utility hypothesis and Savage's Sure-Thing Principle are violated in real life decisions. The popular explanation in terms of 'ambiguity aversion' is not completely accepted. On the other hand, we have recently introduced a notion of 'contextual risk' to mathemat…
Introduces noncommutative geometry for modeling quantum spacetime.
problem Modeling quantum spacetime.
method Operator algebras, K-theory, spectral geometry, quantum groups, and deformation quantization.
result Framework for quantum spacetime.
The operator realizing a Dehn twist in quantum Teichmuller theory is diagonalized and continuous spectrum is obtained. This result is in agreement with the expected spectrum of conformal weights in quantum Liouville theory at c>1. The completeness condition of the eigenvectors includes the integration measure which app…
A general theory of quantum spinor structures on quantum spaces is presented, within the conceptual framework of the formalism of quantum principal bundles. Quantum analogs of all basic objects of the classical theory are constructed and analyzed. This includes Laplace and Dirac operators, quantum versions of Clifford …
Quantum physics model uses knot theory for fragile topology.
problem Modeling quantum physics' fragile topology.
method Knot theoretic algorithm.
result Quantum physics' fragile topology modeled.
Abstract: Topological quantum field theory connects graph evaluations to polynomial identities.
problem Graph evaluations in topological quantum field theory.
method Relates SO(3) topological quantum field theory trace evaluations to topological Tutte polynomial evaluations.
result Generalizes the Tutte golden identity for graphs on the torus.
Quantum field theory connects Riemannian geometry to quantum fluctuations.
problem Generating Riemannian structures from quantum fluctuations.
method QFT approach to Riemannian Geometry, focusing on Ricci curvature.
result Ricci curvature is crucial in generating Riemannian structures.
Quantum Kirwan maps between K-theories of G-varieties and GIT quotients.
problem Constructing maps between K-theories of G-varieties and their GIT quotients.
method Formal construction of maps in quantum K-theory, using equivariant and non-equivariant quantum K-theory.
result Presentation of quantum K-theory for smooth proper toric DM stacks.
This paper applies quantum theory to cost accounting, focusing on WIP valuation.
problem Uncertainties in WIP valuation in cost accounting.
method Quantum theory applied to WIP valuation in cost accounting.
result More nuanced understanding of uncertainties in managerial accounting.
Quantum cellular automata form a homology theory.
problem Understanding the topological structure of quantum cellular automata.
method Formal properties of coarse homology theories.
result Quantum cellular automata naturally form the degree-zero part of a coarse homology theory.
Quantum surgery formulas link statistics and topology.
problem Formulate constraints for quantum statistics of entangled systems.
method Geometric-topology surgery theory on spacetime manifolds.
result New quantum surgery formulas and constraints derived.
The study examines how quantum resources enhance the complexity of quantum circuits.
problem Quantum resource enhancement on circuit complexity.
method Utilizing quantum resource theories, the study analyzes statistical complexities of quantum circuits with limited quantum resources.
result Bounds for statistical complexities of quantum circuits are derived and applied to specific cases.
Paper compares algebraic quantum field theories and factorization algebras on Lorentzian manifolds.
problem Relationship between algebraic quantum field theories and factorization algebras on Lorentzian manifolds.
method Developed functorial constructions under natural hypotheses, including local constancy and descent axioms.
result Equivalence theorem between algebraic quantum field theories and prefactorization algebras.
We give a construction of the abelian Chern-Simons gauge theory from the point of view of a 2+1 dimensional topological quantum field theory. The definition of the quantum theory relies on geometric quantization ideas which have been previously explored in connection to the nonabelian Chern-Simons theory [JW,ADW]. We f…
BCIQT model improves ML prediction effectiveness using quantum theory.
problem Improving prediction effectiveness in machine learning models.
method Proposes Binary Classifier Inspired by Quantum Theory (BCIQT) model.
result BCIQT model outperforms state-of-the-art models in recall.
Introduces geometric quantization and Witten's quantum invariants.
problem None explicitly stated; focuses on introduction.
method Expository introduction to geometric quantization and Witten's quantum invariants.
result Introduction to geometric quantization and Witten's quantum invariants.
Study Vassiliev invariants for virtual knots, expanding quantum theory.
problem Understanding Vassiliev invariants for virtual knots.
method Define chord diagrams, weight systems, and Lie algebra weight systems for rotational virtual knots.
result Extended quantum invariants capture more information than standard invariants.
A quantum reinforcement learning algorithm reduces sample complexity.
problem Quantum reinforcement learning under model-free settings with quantum oracle access.
method Quantum Natural Policy Gradient (QNPG) algorithm replacing random sampling with deterministic gradient estimation.
result QNPG achieves a sample complexity of ildeO(ε−1.5) for queries to the quantum oracle, significantly improving classical lower bound. Quantum Teichmüller invariants studied for 3-manifolds.
problem Quantum invariants of 3-manifolds.
method Characterization through intertwiners and topological quantum field theories.
result Invariants of mapping tori defined by traces of intertwiners.
String theory connects lattice models, links, and geometric Langlands.
problem Connecting lattice models, links, and geometric Langlands.
method T-duality and worldvolume theories in string theory.
result Unified understanding of various mathematical concepts.
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…
AI in finance uses quantum logic for better decision-making.
problem Improving financial decision-making models using AI.
method Application of quantum logic in machine learning techniques.
result Advantages of quantum-inspired neural networks in finance.
Quantum Kerr learning shows enhancements in convergence and generalization for kernel-based methods.
problem Improving convergence and generalization in kernel-based methods for quantum computing.
method Combining quantum mechanics with neural tangent kernel theory and first-order perturbation theory.
result Quantum enhancements in terms of convergence time and generalization error.