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At least 19 records

Improving modular bootstrap bounds with integrality

We propose methods that efficiently impose integrality — i.e., the condition that the coefficients of characters in the partition function must be integers — into numerical modular bootstrap. We demonstrate the method with a number of examples where it can be used to strengthen modular bootstrap results. First, we show that, with a mild extra assumption, imposing integrality improves the bound on the maximal allowed gap in dimensions of operators in theories with a U(1) c symmetry at c = 3, and reduces it to the value saturated by the SU(4) 1 WZW model point of c = 3 Narain lattices moduli space. Second, we show that our method can be used to eliminate all but a discrete set of points saturating the bound from previous Virasoro modular bootstrap results. Finally, when central charge is close to 1, we can slightly improve the upper bound on the scaling dimension gap.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Emergence of the polydeterminant in QCD

A generalization of the determinant appears in particle physics in effective Lagrangian interaction terms that model the chiral anomaly in quantum chromodynamics (Giacosa et al. in Phys Rev D 97(9):091901, 2018, Phys Rev D 109(7):L071502, 2024), in particular in connection to mesons. This polydeterminant function, known in the mathematical literature as a mixed discriminant, associates N distinct N x N complex matrices into a complex number and reduces to the usual determinant when all matrices are taken as equal. Here, we explore the main properties of the polydeterminant applied to (quantum) fields by using a formalism and a language close to high-energy physics approaches. We discuss its use as a tool to write down novel chiral anomalous Lagrangian terms and present an explicit illustrative model for mesons. Finally, the extension of the polydeterminant as a function of tensors is shown.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

On the factorization of block-tridiagonals without storage constraints

In many programs solving difference equations, problem size is restricted by the number of available memory cells. A strategy has been developed to permit trade-offs between the number of floating point operations required and storage requirements for the solution of certain problems such as block tridiagonal systems of equations. This is done by recomputing some intermediate results instead of storing them. Reducing the storage to the square root of the current requirement will roughly double the number of computations. In theory, if m is the order of each sub-matrix in the block tridiagonal matrix, one can solve any linear system with only 5 sq m + 1 temporary storage cells. This method lends itself to efficient use on computers with parallel processing or vector processing architectures. On these computers the larger number of floating point operations is more than offset by the decrease in I/O and the increased percentage of vector operations made possible by this algorithm.

Merriam, M. L.↗

Intelligent feature selection techniques for pattern classification of Lamb wave signals

Lamb wave interaction with flaws is a complex, three-dimensional phenomenon, which often frustrates signal interpretation schemes based on mode arrival time shifts predicted by dispersion curves. As the flaw severity increases, scattering and mode conversion effects will often dominate the time-domain signals, obscuring available information about flaws because multiple modes may arrive on top of each other. Even for idealized flaw geometries the scattering and mode conversion behavior of Lamb waves is very complex. Here, multi-mode Lamb waves in a metal plate are propagated across a rectangular flat-bottom hole in a sequence of pitch-catch measurements corresponding to the double crosshole tomography geometry. The flaw is sequentially deepened, with the Lamb wave measurements repeated at each flaw depth. Lamb wave tomography reconstructions are used to identify which waveforms have interacted with the flaw and thereby carry information about its depth. Multiple features are extracted from each of the Lamb wave signals using wavelets, which are then fed to statistical pattern classification algorithms that identify flaw severity. In order to achieve the highest classification accuracy, an optimal feature space is required but it’s never known a priori which features are going to be best. For structural health monitoring we make use of the fact that physical flaws, such as corrosion, will only increase over time. This allows us to identify feature vectors which are topologically well-behaved by requiring that sequential classes “line up” in feature vector space. An intelligent feature selection routine is illustrated that identifies favorable class distributions in multi-dimensional feature spaces using computational homology theory. Betti numbers and formal classification accuracies are calculated for each feature space subset to establish a correlation between the topology of the class distribution and the corresponding classification accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Large-Scale Refinement of Metal-Organic Framework Structures Using Density Functional Theory

Efforts to computationally characterize large numbers of nanoporous materials often rely on databases of experimentally resolved crystal structures. The accuracy of experimental crystal structures used in such calculations has a significant impact on the reliability of the results. Here in this work, we report structures optimized using periodic density functional theory (DFT) for more than 800 experimentally synthesized metal-organic frameworks (MOFs). Many MOFs changed significantly upon structural optimization, particularly materials that were crystallographically resolved in their solvated form. For each MOF, we simulated the adsorption of CH 4 and CO 2 using grand canonical Monte Carlo both before and after DFT optimization. The DFT optimization has a large impact on simulated gas adsorption in some cases – for example, CO 2 loading at 1 bar changed by more than 25% in over 25% of the MOFs we considered.

36 MATERIALS SCIENCE↗

Simulation of Nonlinear Instabilities in an Attachment-Line Boundary Layer

The linear and the nonlinear stability of disturbances that propagate along the attachment line of a three-dimensional boundary layer is considered. The spatially evolving disturbances in the boundary layer are computed by direct numerical simulation (DNS) of the unsteady, incompressible Navier-Stokes equations. Disturbances are introduced either by forcing at the in ow or by applying suction and blowing at the wall. Quasi-parallel linear stability theory and a nonparallel theory yield notably different stability characteristics for disturbances near the critical Reynolds number; the DNS results con rm the latter theory. Previously, a weakly nonlinear theory and computations revealed a high wave-number region of subcritical disturbance growth. More recent computations have failed to achieve this subcritical growth. The present computational results indicate the presence of subcritically growing disturbances; the results support the weakly nonlinear theory. Furthermore, an explanation is provided for the previous theoretical and computational discrepancy. In addition, the present results demonstrate that steady suction can be used to stabilize disturbances that otherwise grow subcritically along the attachment line.

Joslin, Ronald D.↗

Hardware-Conscious Optimization of the Quantum Toffoli Gate

While quantum computing holds great potential in combinatorial optimization, electronic structure calculation, and number theory, the current era of quantum computing is limited by noisy hardware. Many quantum compilation approaches can mitigate the effects of imperfect hardware by optimizing quantum circuits for objectives such as critical path length. Few approaches consider quantum circuits in terms of the set of vendor-calibrated operations (i.e., native gates) available on target hardware. This manuscript expands the analytical and numerical approaches for optimizing quantum circuits at this abstraction level. We present a procedure for combining the strengths of analytical native gate-level optimization with numerical optimization. Although we focus on optimizing Toffoli gates on the IBMQ native gate set, the methods presented are generalizable to any gate and superconducting qubit architecture. Our optimized Toffoli gate implementation demonstrates an 18% reduction in infidelity compared with the canonical implementation as benchmarked on IBM Jakarta with quantum process tomography. Assuming the inclusion of multi-qubit cross-resonance (MCR) gates in the IBMQ native gate set, we produce Toffoli implementations with only six multi-qubit gates, a 25% reduction from the canonical eight multi-qubit implementations for linearly connected qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

On the inversion of block tridiagonals without storage constraints

A strategy was developed to permit trade-offs between the number of floating point operations required and the storage requirements for the solution of certain difference problems, such as block tridiagonal systems of equations. This is done by recomputing some intermediate results instead of storing them. Reducing the storage to the square root of the current requirement roughly doubles the number of computations. Reducing the storage more than this tends to make the number of computations prohibitively large. In theory, if m is the order of each sub-matrix in the block tridiagonal matrix, one can solve any linear system with only 5m(2) + 1 temporary storage cells. In many cases m is a constant and quite small. For example, in solving a factored form of the three-dimensional Navier-Stokes equations, the size m of the block tridiagonals is 5. This method lends itself to efficient use on computers with parallel processing or vector processing architectures. On these computers the larger number of floating point operations is more than offset by the decrease in I/O and the increased percentage of vector operations made possible by this algorithm.

Merriam, M. L.↗

Constraining $\mathcal{f(R)}$ gravity with a $\mathcal{k}$-cut cosmic shear analysis of the Hyper Suprime-Cam first-year data

Here, using Subaru Hyper Suprime-Cam (HSC) year 1 data, we perform the first k-cut cosmic shear analysis constraining both Λ CDM and f(R) Hu-Sawicki modified gravity. To generate the f(R) cosmic shear theory vector, we use the matter power spectrum emulator trained on COLA (COmoving Lagrangian Acceleration) simulations [Phys. Rev. D 103, 123525 (2021)]. The k-cut method is used to significantly down-weight sensitivity to small scale (k > 1h Mpc -1 ) modes in the matter power spectrum where the emulator is less accurate, while simultaneously ensuring our results are robust to baryonic feedback model uncertainty. We have also developed a test to ensure that the effects of poorly modeled small scales are nulled as intended. For Λ CDM we find S 8 =σ 8 (Ω m /0.3) 0.5 =0.789$^{+0.039}_{-0.022}$, while the constraints on the f(R) modified gravity parameters are prior dominated. In the future, the k-cut method could be used to constrain a large number of theories of gravity where computational limitations make it infeasible to model the matter power spectrum down to extremely small scales.

79 ASTRONOMY AND ASTROPHYSICS↗

Robust stability of linear systems: Some computational considerations

The cases of both additive and multiplicative perturbations were discussed and a number of relationships between the two cases were given. A number of computational aspects of the theory were also discussed, including a proposed new method for evaluating general transfer or frequency response matrices. The new method is numerically stable and efficient, requiring only operations to update for new values of the frequency parameter.

Laub, A. J.↗

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^(8) determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

Quantum Computing↗

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^(8) determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

Quantum Computing↗

Efficient Implementation for Unitary Coupled Cluster State Preparation for Near-Term Quantum Computers

Unitary coupled cluster theory (UCC) is a common wave function ansatz for quantum simulation of molecular electronic structure using the variational quantum eigenvalue solver (VQE). Even for small molecules using a double-ζ basis, the number of variational parameters required to minimize the electronic energy (i.e., optimize the circuit) is large and beyond the reach of current quantum computers. For example, a circuit simulating C2 using the UCCSD ansatz and the cc-pVDZ basis set with frozen-core will require over 10,000 variational parameters and a Hilbert space of over 10^8 determinants. To make progress on simulating such molecular systems on near-term quantum computers, we explore how much of the optimization can be approximately prepared with classical simulation while reducing the number of optimization steps performed on a quantum device. Recently, Chen, Cheng, and Freericks [J. Chem. Theory Comput. 2021, 17, 841-847] presented an algorithm for the factorized form of the UCC ansatz that allows for efficient UCC optimizations on classical hardware. We flip the algorithm around and use it to prepare approximate quantum circuits for systems that require a large number of qubits to represent. We will present results from our implementation and discuss strategies for incorporating this implementation for algorithms involving near-term quantum computers.

J Wayne Mullinax↗

Experimental and theoretical investigations in two-dimensional transonic flow.

Experimental and theoretical results are presented from a study of the flow over a family of transonically scaled circular-arc bodies mounted in a solid-wall wind tunnel. Data are presented for Reynolds numbers between 30,000 and 3,600,000, based on chord. The high Reynolds number results are compared with computations based on inviscid theory, and are used to investigate transonic similarity and the behavior of the flow near choking. The results at low Reynolds number are used to demonstrate the effect of viscosity on the overall flowfield, and comparisons are made with existing laminar viscous/inviscid interaction theory.

Collins, D. J.↗

Investigation of the Laminar Aerodynamic Heat-transfer Characteristics of a Hemisphere-cylinder in the Langley 11-inch Hypersonic Tunnel at a Mach Number of 6.8

A program to investigate the aerodynamic heat transfer of a nonisothermal hemisphere-cylinder has been conducted in the Langley 11-inch hypersonic tunnel at a Mach number of 6.8 and a Reynolds number from approximately 0.14 x 10(6) to 1.06 x 10(6) based on diameter and free-stream conditions. The experimental heat-transfer coefficients were slightly less over the whole body than those predicted by the theory of Stine and Wanlass (NACA technical note 3344) for an isothermal surface. For stations within 45 degrees of the stagnation point the heat-transfer coefficients could be correlated by a single relation between local Stanton number and local Reynolds number. Pitot pressure profiles taken at a Mach number of 6.8 on a hemisphere-cylinder have verified that the local Mach number or velocity outside the boundary layer required in the theories may be computed from the surface pressures by using isentropic flow relations and conditions immediately behind a normal shock. The experimental pressure distribution at Mach number of 6.8 is closely predicted by the modified Newtonian theory.

Crawford, Davis H↗

Ab Initio Methods for L-edge X-ray Absorption Spectroscopy

The theoretical prediction of X-ray absorption spectra (XAS) has become common- place in electronic structure theory. The ability to better model and understand L-edge spectra is of great interest in the study of transition metal complexes and a wide variety of solid state materials. However, until recently few rst-principles works have mod- eled L-edge XAS due to the presence of strong spin-orbit coupling in the 2p orbitals which splits the observed peaks into multiple groups of features. Therefore, a proper description of spin-orbit coupling is vital for the successful prediction of L-edge spectra. A number of new approaches that incorporate spin-orbit coupling have recently made advances in the computation of L-edge spectra. In this review, we describe recent work in computational L-edge XAS and how these methods may continue to improve in the future. Comparison of the advantages and disadvantages of the various approaches are considered, with special attention to not only the computational cost of the level of theory, but also the various approaches that can be used to compute the absorption spectra with a large number of high energy excited states.

Kasper, Joseph M.↗

Revisit of polystyrene-modified fullerene core stars: A computational study

Density functional theory (DFT) calculations have been used to clarify the number of poly(styryl) lithium anions that are grafted onto C 60 fullerene. The computational results suggest that 6-arm-grafted C 60 fullerene is the most thermodynamically favorable, and the grafted C 60 fullerene with arms more than 6 is only achievable under certain circumstances. This observation is consistent with the previous experiments [Macromolecules 2013; 46:7451–57.]. Both electronic effect and steric effect have been thoroughly examined and they are found to play different roles in the arm-grafted C 60 fullerene. Our study will pave a way for the future architecture of polymers on C 60 fullerene and the like.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Subsolidus convection in the mantles of terrestrial planets

The role of heat transport by solid state mantle convection in determining the past and present thermal states of terrestrial planets is examined. Mantle convection models have relied on two-dimensional and axisymmetric three-dimensional numerical calculations incorporating the temperature and pressure dependence of mantle rheology and its non-Newtonian nature. Convection at high Rayleigh numbers has been investigated through theoretical scaling arguments and boundary layer theories; nevertheless, computational limits prevent modeling of the fully three-dimensional, time-dependent, very high Rayleigh number convection which probably prevails in terrestrial planets. Radar measurements of Venus, as well as Voyager exploration of the Galilean satellites, should also provide information on mantle convection.

Schubert, G.↗