Train quantum networks to implement target algorithms.
problem Designing quantum computers with minimal external control.
method Supervised quantum gate training for subset evolution.
result Quantum networks implement target algorithms efficiently.
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.
169,341 papers · 148 categories
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48 results for “quantum computer construction”
Universal Braiding Quantum Gatesquant-ph
Simple construction for universal quantum gates.
problem Designing efficient quantum gates for topological computers.
method Demonstrated a simple construction for unitary solutions of the braided Yang-Baxter equation in any dimension.
result Proved the existence of universal quantum gates in any dimension.
MBQC linked to CQCA, yielding efficient Ansätze.
problem Quantum computation efficiency and Ansatz adaptation.
method Relating MBQC to CQCA and constructing Ansätze.
result MBQC Ansätze can lead to different performances on learning tasks.
Quantum algorithm improves portfolio construction accuracy.
problem Efficiently constructing portfolios with real-world constraints.
method Sampling-based CVaR Variational Quantum Algorithm (VQA) combined with local-search post-processing.
result Achieved a relative solution error of 0.49% on IBM Heron processors.
Quantum computing speeds up multi-period asset allocation.
problem High computational complexity in classic computing for multi-period asset allocation.
method Applied quantum computing to simulate multi-asset portfolio using historic data.
result Quantum computing offers significant advantages over classical computing in finance.
Quantum walk algorithm optimizes quantum state preparation for financial simulations.
problem Efficiently loading classical data into quantum states for quantum computers.
method Split-step quantum walks (SSQW) to design parameterized quantum circuits (PQC).
result SSQW facilitates generating desired probability amplitude distributions for quantum simulations.
Topological Quantum Computationquant-ph
The theory of quantum computation can be constructed from the abstract study of anyonic systems. In mathematical terms, these are unitary topological modular functors. They underlie the Jones polynomial and arise in Witten-Chern-Simons theory. The braiding and fusion of anyonic excitations in quantum Hall electron liqu…
This review covers quantum computing applications in finance and blockchain.
problem Challenges in finance and blockchain security with quantum computing.
method Systematic review of recent quantum finance and blockchain work.
result Quantum-resistant blockchain systems and security measures.
Researchers prove quantum invariants remain hard even when restricted.
problem Computing quantum invariants on 3-manifolds with specific restrictions.
method Using Heegaard splittings and Hempel distance, they construct a hyperbolic 3-manifold with same invariant.
result Proving hardness of computing quantum invariants is preserved under specific restrictions.
A quantum N-dimer modelmath.QA
Quantum model for knotted graphs from knot theory.
problem Constructing an isotopy invariant polynomial for knotted bipartite ribbon graphs.
method Applying quantum topology to construct an isotopy invariant polynomial.
result Computed the expected number of loops in the double dimer model.
Geometric models create fractional quantum anyons.
problem Constructing fractional quantum anyons.
method 4D edge-cone orbifold geometries with embedded 2D surfaces.
result Anyon states arise from braid representations of surface braids.
Quantum invariant derived from ternary cohomology of self-distributive structures.
problem Defining and proving a quantum invariant from ternary cohomology.
method Constructing a ribbon category from a TSD set, showing it coincides with the cocycle invariant.
result The ribbon cocycle invariant is a quantum invariant.
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 link invariants derived from skein algebras.
problem Defining invariants for framed links with SL2 local systems.
method Theory of representations of stated skein algebras, quantum coadjoint action, Drinfeld double, Bonahon-Wong quantum trace.
result Explicit formulas for link invariants and alternative proof of Murakami-Murakami relation.
Quantum computing tackles non-convex portfolio optimization with cardinality constraints.
problem Non-convex portfolio optimization problems in asset management.
method Application of quantum annealing with non-linear cardinality constraints.
result Quantum portfolio optimization yields smaller, more profitable portfolios.
New classical algorithm outperforms quantum in neural network subnetwork selection.
problem Selecting sparse subnetworks from large neural networks efficiently.
method Quantum-inspired classical algorithm using ridgelet transform sampling.
result Runs in polynomial time, outperforming naive classical methods.
Quantum computers outperform classical methods in density modeling.
problem Density modeling with quantum computers.
method Quantum-classical separation for density modeling.
result Quantum computers offer a super-polynomial advantage over classical algorithms for density modeling.
New quantum kernels avoid overfitting by combining local and global components.
problem Exponential concentration in quantum kernels leads to overfitting.
method Local-global quantum kernels combining small subsystem and full-system measurements.
result Demonstrated benign overfitting in local-global quantum kernels.
Logarithmic invariant for restricted quantum sl(2) constructed.
problem Constructing a logarithmic invariant for a specific quantum group.
method Combining a universal invariant and a modified trace, defined for a 3-manifold and link.
result A new logarithmic invariant for restricted quantum sl(2) at a 2p-th root of unity.
Quantum entanglement is linked to topological braiding through Yang-Baxter equations.
problem Understanding the relationship between quantum entanglement and topological braiding.
method Viewing unitary entangling operators as braiding operators and using Yang-Baxter equations.
result Quantum entanglement is necessary for forming invariants of knots, as shown by solutions to the Yang-Baxter Equation.
Quantum computing speeds up option pricing for multiple assets.
problem High-dimensional integration bottleneck in option pricing.
method Calibrated marginal distributions, Gaussian copula, QAMC with QAE.
result QAMC reduces integration queries by 10-100 times for similar precision.
Quantum kernels can be efficiently embedded into classical feature spaces.
problem Can all quantum kernels be efficiently embedded into classical feature spaces?
method Invoking computational universality and using techniques like random Fourier features, the authors show that certain classes of quantum kernels can be efficiently embedded.
result For shift-invariant and composition kernels, embedding quantum kernels are universal and efficient.
In quantum computation, series of quantum gates have to be arranged in a predefined sequence that led to a quantum circuit in order to solve a particular problem. What if the sequence of quantum gates is known but both the problem to be solved and the outcome of the so defined quantum circuit remain in the shadow? This…
Quantum algorithms improve perceptron learning efficiency.
problem Improving quantum algorithms for perceptron learning.
method Revisiting and correcting a flawed quantum version space perceptron algorithm, proposing quantum-enhanced cutting-plane algorithms.
result Improved complexity bounds for quantum perceptron learning.
Iterative Quantum Feature Mapsquant-ph
A new hybrid framework reduces quantum runtime and noise effects.
problem Challenges in deploying deep QFMs on real quantum hardware.
method Iterative Quantum Feature Maps (IQFMs) combining shallow QFMs and classical augmentation weights.
result Numerical experiments show IQFMs outperforming quantum convolutional neural networks.
Quantum machine learning offers advantages for broader learning tasks.
problem Demonstrate QML advantage over classical methods for general learning tasks.
method Construct a new family of supervised learning tasks and prove their hardness.
result Prove provable advantage of QML based on general quantum computational advantages.
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.
Quantum invariant constructed for sutured 3-manifolds using Hopf superalgebra.
problem Quantum invariants for balanced sutured 3-manifolds with structure.
method Involutive Hopf superalgebra and Fox calculus to compute the invariant.
result Invariant is a normalization of Reidemeister torsion when is Borel subalgebra of .
Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learningquant-ph
Quantum circuits explained using Shapley values for better understanding.
problem Improving the explainability of quantum machine learning circuits.
method Applying Shapley values to quantify gate importance in quantum circuits.
result Quantum circuits can be explained by their gate importance, enhancing understanding and interpretability.
Quantum hybrid vision transformers improve event classification in high energy physics.
problem Excessive computational resources for training and deploying vision transformer models.
method Constructed quantum hybrid vision transformers for high energy physics event classification.
result Quantum hybrid models achieve comparable performance to classical models with fewer parameters.
Quantum computing speeds up risk analysis by efficiently sampling copulas.
problem Efficiently modeling tail dependence and risk measures in financial risk analysis.
method Quantum computing implementation of copula models for risk aggregation.
result The MB11 copula family is suitable for capturing tail dependence structures in risk factors.
Quantum machine learning uses quantum cross entropy to minimize loss, but measurement loss affects this process.
problem Quantum machine learning's loss minimization through cross entropy is affected by measurement outcomes.
method Defined quantum cross entropy, proved its lower bounds, and investigated its relation to quantum fidelity and likelihood.
result Quantum cross entropy is lower-bounded by negative log-likelihood when derived from quantum data, but measurement outcomes can cause loss.
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.
Smoothly prepares quantum states for robust machine learning.
problem Efficiently preparing quantum states for machine learning.
method Smoothed analysis to prove constant query state preparation.
result State preparation can be achieved with constant queries under realistic noise conditions.
Graph potentials link to topological QFTs, with computational methods.
problem Defining a topological quantum field theory using graph potentials.
method Using colored trivalent graphs and birational type to define a topological QFT.
result Graph potentials' birational type depends on the graph's homotopy type.
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.
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.
Constructs a path integral for quantum Mabuchi K-energy.
problem Quantum corrections to classical Mabuchi K-energy.
method Coupling Liouville action and Mabuchi K-energy via probabilistic tools.
result Obtains a path integral with Weyl anomaly including K-energy term.
Quantum machine learning tackles large datasets with randomized measurements.
problem Efficiently process large, high-dimensional datasets on quantum computers.
method Randomized measurements to scale linearly with dataset size and quadratic for post-processing.
result Substantial speed-up for noisy quantum computers, enabling image classification.
Quantum reservoir computing tackles noisy quantum computers for temporal tasks.
problem Efficiently process input sequences on noisy quantum computers.
method Quantum reservoir computing using dissipative quantum dynamics.
result Small and noisy quantum reservoirs can handle high-order nonlinear temporal tasks.
Quantum computing techniques improve graph analysis and community detection.
problem Analyzing large graphs efficiently and accurately.
method Used quantum annealing and quantum gate computers for community detection and regularity checking.
result Demonstrated the effectiveness of quantum computing in solving complex graph problems.
Researchers successfully implemented quantum autoencoders using quantum adders in a cloud quantum computer.
problem Reducing resource usage in quantum computations.
method Experimental implementation of quantum autoencoders using approximate quantum adders in a cloud quantum computer.
result Experimental fidelities are in good agreement with theoretical predictions, proving the feasibility of quantum autoencoders via quantum adders.
New quantum invariants for planar knotoids improve knot classification.
problem Classifying and distinguishing planar knotoids with up to five crossings.
method Define biframed planar knotoids and construct new invariants.
result Improved classification of planar knotoids with up to five crossings.
Develops an analytic theory for quantum imaginary time evolution.
problem Lack of a first-principle understanding of quantum imaginary time evolution.
method Interprets QITE as a form of VQA trained with QNGD and connects it to the geometric geodesic distance in the quantum Fisher information metric.
result QITE converges faster than vanilla gradient descent-based VQAs, though the advantage is suppressed by Hilbert space dimensionality.
Quantum character varietiesmath.QA
Quantum character varieties unify four construction methods.
problem No specific problem stated; unification of approaches.
method Four different approaches to construction.
result Unified understanding of quantum character varieties.
Constructs 3D topological field theories from a specific quantum group, linking to physics invariants.
problem Developing topological field theories from non-semisimple quantum groups.
method Using the unrolled quantum group of and a relative modular structure on weight modules.
result Establishes a connection between constructed invariants and physicists' -invariants.
Zesting affects Reshetikhin-Turaev invariants of links and 3-manifolds.
problem Understanding how zesting affects Reshetikhin-Turaev invariants.
method Developed a local formalism to compute tangle invariants and link invariants.
result Zesting contributes to complexity-theoretic hierarchies of topological field theories.
Quantum computing offers new solutions for finance problems.
problem Challenging classical computational problems in finance.
method Quantum algorithms for finance applications.
result Potential benefits for financial services.