No chiral field theory for quantum spin chain limits.
problem Chiral conformal field theory limits of quantum spin chains.
method Block spin renormalization, Hamiltonian analysis.
result No continuous limit to chiral field theory.
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48 results for “quantum chain”
Generative Neural Samplers for the Quantum Heisenberg Chaincond-mat.stat-mech
Generative neural samplers estimate quantum spin system properties.
problem Estimating observables for quantum spin systems.
method Autoregressive models using Suzuki-Trotter transformation.
result Results for energy, specific heat, and susceptibility are in good agreement with Monte Carlo methods.
New quantum code lacks sparse lift.
problem Existence of sparse lifts for quantum codes.
method Constructed a sparse chain complex without a sparse lift.
result Found a quantum code without a sparse lift.
Quantum algorithms for financial derivatives and credit risk.
problem Estimating credit risk and option pricing in realistic financial models.
method Developed a regime switching volatility model for financial markets, using a Markov chain to determine volatility parameters.
result Quantum algorithms can be applied to realistic financial models, bringing quantum computing closer to practical applications.
Constructs manifolds from quantum codes with novel geometric properties.
problem Creating manifolds with specific geometric constraints.
method Reverse engineering manifolds from quantum code chain complexes.
result First examples of power law systolic freedom.
TensorNetwork speeds up quantum spin chain calculations using GPU.
problem Efficiently approximating ground states of quantum spin chains.
method Tree tensor network (TTN) algorithm implemented in TensorNetwork.
result Significant computational speed-ups using GPUs (up to 100x faster).
qBitcoin uses quantum teleportation for secure, fast transactions.
problem Preventing double-spending in quantum cash systems.
method Uses quantum teleportation and quantum chain for secure, fast transactions.
result Security and speed of qBitcoin are guaranteed by quantum information theory.
Quantum systems on coadjoint orbits yield spectra matching Dolbeault and de Rham indices.
problem Finding exact spectra of generalized Laplace operators on coadjoint orbits.
method Truncation of 1D sigma models and nonlinear chiral multiplets.
result Exact spectra of spin chain Hamiltonians match Dolbeault and de Rham indices of target spaces.
The paper calculates the asymptotics of quantum invariants for Whitehead chains.
problem Quantum invariants of Whitehead chains with colored clasps.
method Asymptotic analysis of colored Jones polynomials, considering limiting ratios of sequences.
result The exponential growth rate of invariants matches the hyperbolic volume of link complements.
New quantum integrals discovered for a spin chain model.
problem Exploring quantum integrals for a spin chain model.
method Using surface defects and observables in 4D super-QCD.
result First construction of quantum integrals and their joint eigenvectors.
New approach connects quantum phases to VQA trainability, enabling better scaling.
problem Scalability issues in VQAs, especially barren plateaus.
method Analog VQA ansätze composed of quenches of a disordered Ising chain, tuning disorder strength.
result Thermalized and MBL phases reach maximal expressivity at large , but barren plateaus emerge at smaller in the thermalized phase.
We prove Tsygan's formality conjecture for Hochschild chains of the algebra of functions on an arbitrary smooth manifold M using the Fedosov resolutions proposed in math.QA/0307212 and the formality quasi-isomorphism for Hochschild chains of R[[y_1, ..., y_d]] proposed in paper math.QA/0010321 by Shoikhet. This result …
The Jones-Wenzl projectors play a central role in quantum topology, underlying the construction of SU(2) topological quantum field theories and quantum spin networks. We construct chain complexes whose graded Euler characteristic is the "classical" projector in the Temperley-Lieb algebra. We show that they are homotopy…
Quantum Bayesian Computationstat.ML
QBC uses quantum computers to speed up Bayesian computation.
problem Exponential speed-up in Bayesian computation.
method Quantum von Neumann measurement for simulating ML algorithms.
result Quantum versions of regression, Gaussian processes, and SGD.
A new penalty-free method optimizes portfolios without quantum annealing penalties.
problem Optimizing portfolios with quantum annealing penalties.
method Removing the penalty term and using a classical feasibility projector.
result Significant reduction in chain-break fractions and post-processed regret.
Quantum hardware accelerates training of Boltzmann machines, improving sampling and learning.
problem Training fully visible Boltzmann machines with high-energy barriers.
method Benchmarked quantum annealing hardware for training Boltzmann machines, comparing quantum and classical distributions.
result Quantum hardware can improve training of Boltzmann machines, especially for hard problems.
New algorithms improve MCMC efficiency for complex distributions.
problem High variance and low effective sample size in MCMC samplers.
method Antithetic Riemannian Manifold and Quantum-Inspired Hamiltonian Monte Carlo.
result Improved effective sample size and variance reduction.
Quantizes the relationship between Koszul and Schouten brackets in Poisson geometry.
problem Quantizing the relationship between Koszul and Schouten brackets in Poisson geometry.
method Employing Voronov's thick morphism technique and quantum Mackenzie-Xu transformations in the framework of -algebroids.
result Quantizes the -morphism into a single linear operator, a formal Fourier integral operator.
Quantum computing uses Bianchi groups to build gates.
problem Building universal quantum gates from Bianchi groups.
method Using subgroups of Bianchi groups to derive quantum gate generators.
result Demonstrated the use of Bianchi groups for quantum computing.
Quantum Inception Scorequant-ph
Proposes qIS for quantum generative models, extending classical inception score.
problem Develop a metric to evaluate quantum generative models.
method Introduces qIS, relating quality to Holevo information of quantum channel.
result qIS enhances the quality of quantum generative models, showing physical limitations.
Paper develops security model and pricing for stable digital currency in quantum blockchain network.
problem Securing and pricing stable digital currency in a quantum blockchain network.
method Developed a block-based quantum channel networking technology and a FinTech platform model with dynamic pricing.
result Established a generalized IoB security model using quantum channel networking and QKD.
We prove that Morrison and Nieh's categorification of the su(3) quantum knot invariant is functorial with respect to tangle cobordisms. This is in contrast to the categorified su(2) theory, which was not functorial as originally defined. We use methods of Bar-Natan to construct explicit chain maps for each variation of…
Flow-VQE uses generative flows to optimize VQE efficiently.
problem Complex objective functions and expensive optimization in VQE.
method Generative normalizing flows with parameterized quantum circuits.
result Flow-VQE accelerates convergence and reduces circuit evaluations.
Quantum machine learning classification depends on mutual informations between state and parameter spaces.
problem Generalization in quantum machine learning models.
method Link between quantum machine learning and quantum hypothesis testing, using mutual informations.
result Quantum classifier accuracy and generalization depend on mutual informations between state and parameter spaces.
Quantum algorithm approximates Khovanov homology ranks.
problem Efficient computation of Khovanov homology ranks.
method Novel quantum algorithm with pre-thermalization procedure.
result Additive approximations to Khovanov homology ranks are hard problems.
Quantum annealer speeds up RBM training for image classification.
problem Training RBM with contrastive divergence (CD) is slow and computationally expensive.
method Used D-Wave 2000Q quantum annealer to calculate model expectation of gradient learning for RBM.
result Quantum training yields similar classification performance to CD but faster.
Quantum algorithm speeds up Gibbs partition function estimation.
problem Estimating partition functions in sublinear time.
method Sublinear-time quantum algorithm using quantum phase and amplitude estimation.
result First sublinear-time speed-up for partition function estimation.
Solves geodesics and Laplace-Beltrami spectrum on flag manifolds.
problem Geodesics and Laplace-Beltrami spectrum on flag manifolds.
method Invariant metrics and finite-dimensional approximations.
result Explicit solutions for geodesics and spectrum.
Active learning of Boltzmann samplers and potential energies with quantum mechanical accuracyphysics.chem-ph
New method combines deep learning and quantum mechanics for efficient molecular statistics.
problem Computational expense in extracting statistics from molecular systems.
method Adaptive Markov chain Monte Carlo with Normalizing Flow and MLP for quantum accuracy.
result Rapid convergence to Boltzmann distribution and accurate thermodynamic observables.
The Temperley-Lieb algebra is a fundamental component of SU(2) topological quantum field theories. We construct chain complexes corresponding to minimal idempotents in the Temperley-Lieb algebra. Our results apply to the framework which determines Khovanov homology. Consequences of our work include semi-orthogonal deco…
Quantum methods speed up inference in Markov logic networks.
problem Efficient inference in Markov logic networks (MLNs).
method Analysis of graph structures and application of quantum protocols to Gibbs sampling.
result Exponential speedup in approximate probabilistic inference using quantum methods.
High-fidelity quantum simulations demonstrated on short-coherence hardware.
problem Short coherence times limit the depth of quantum algorithms.
method Fixed State Variational Fast Forwarding (fsVFF) algorithm.
result Simulations of 600 time steps possible, 150x longer than previous methods.
Two link diagrams on compact surfaces are strongly equivalent if they are related by Reidemeister moves and orientation preserving homeomorphisms of the surfaces. They are stably equivalent if they are related by the two previous operations and adding or removing handles. Turaev and Turner constructed a link homology f…
We summarize our axioms for higher categories, and describe the blob complex. Fixing an n-category C, the blob complex associates a chain complex B_*(W;C)$ to any n-manifold W. The 0-th homology of this chain complex recovers the usual topological quantum field theory invariants of W. The higher homology groups should …
In this paper we give a quantum statistical interpretation for the bracket polynomial state sum <K> and for the Jones polynomial. We use this quantum mechanical interpretation to give a new quantum algorithm for computing the Jones polynomial. This algorithm is useful for its conceptual simplicity, and it applies to al…
Deep learning wave function improves quantum chemistry calculations.
problem Solving the electronic Schrödinger equation for complex molecules is computationally expensive.
method PauliNet, a deep learning wave function ansatz that incorporates physics and is trained with VMC.
result PauliNet achieves nearly exact solutions and outperforms other methods for various molecules.
FFT-Accelerated Auxiliary Variable MCMC for Fermionic Lattice Models: A Determinant-Free Approach with Complexitycond-mat.str-el
New MCMC method speeds up quantum physics simulations by a factor of 100.
problem Simulating quantum many-body systems with high computational complexity.
method FFT-accelerated MCMC with coupled particle and auxiliary variables.
result Achieves scaling, significantly faster than traditional methods.
Study integrability of quantized six-vertex model on torus.
problem Integrability of a specific lattice model on a torus.
method Defined layer transfer matrices and tetrahedron equations for admissible graphs.
result Established commutativity of transfer matrices and derived quantum Hamiltonians.
The data of a "2D field theory with a closed string compactification" is an equivariant chain level action of a cell decomposition of the union of all moduli spaces of punctured Riemann surfaces with each component compactified as a pseudomanifold with boundary. The axioms on the data are contained in the following ass…
The paper explores exotic symplectomorphisms and quantum cohomology relations in Fano 3-folds.
problem Existence of exotic symplectomorphisms in Fano 3-folds.
method Construction of -structures, Massey products, Andreadakis-Johnson theory, and analysis of quantum cohomology.
result Existence of exotic symplectomorphisms for certain Fano 3-folds.
D-Wave quantum annealing fails to improve sampling quality from RBMs compared to Gibbs sampling.
problem Improving sampling quality from RBMs using D-Wave quantum annealing.
method Comparison of D-Wave quantum annealing and Gibbs sampling for RBM sampling.
result D-Wave sampling does not significantly improve the number of local valleys compared to Gibbs sampling.
This paper explores Khovanov adequacy in knot theory.
problem Understanding Khovanov homology and its adequacy.
method Using independence complexes and homotopy type calculations.
result Khovanov adequacy is explored within the context of independence complexes and homotopy type of extreme spectra.
Quantum Annealing for Dirichlet Process Mixture Models with Applications to Network Clusteringcond-mat.dis-nn
We developed a new quantum annealing (QA) algorithm for Dirichlet process mixture (DPM) models based on the Chinese restaurant process (CRP). QA is a parallelized extension of simulated annealing (SA), i.e., it is a parallel stochastic optimization technique. Existing approaches [Kurihara et al. UAI2009, Sato et al. UA…
Towards Sampling from Nondirected Probabilistic Graphical models using a D-Wave Quantum Annealercs.LG
Quantum annealer improves classification of handwritten digits.
problem Classical MCMC struggles with missing labels in RBM models.
method Embedding RBM into D-Wave quantum annealer for classification.
result D-Wave QA reduces classification error by more than two times.
The paper concerns a compactification of the isospectral varieties of nilpotent Toda lattices for real split simple Lie algebras. The compactification is obtained by taking the closure of unipotent group orbits in the flag manifolds. The unipotent group orbits are called the Peterson varieties and can be used in the co…
Solves sigma model on U(3)/U(1)^3, describing geodesics and spectrum.
problem Classical and quantum problems for 1D sigma model with specific target space.
method Mapping to Gaudin model, solving polynomial equations.
result Explicit description of geodesics and spectrum found.
In this paper, we begin constructing a new finite-dimensional topological quantum field theory (TQFT) for three-manifolds, based on group PSL(2,C) and its action on a complex variable by fractional-linear transformations, by providing its key ingredient -- a new type of chain complexes. As these complexes happen to be …
HR-calculus enables adaptive processing of quaternion signals.
problem Lack of adaptive processing techniques for quaternion-valued signals.
method Introduction and development of HR-calculus for quaternion algebra.
result Derivation of gradient operator, chain and product derivative rules, and Taylor series expansion for quaternion calculus.