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Nuclear Data Sheets for A=203
Evaluated nuclear structure and decay data for all nuclei with mass number A=203 ( 203 Os, 203 Ir, 203 Pt, 203 Au, 203 Hg, 203 Tl, 203 Pb, 203 Bi, 203 Po, 203 At, 203 Rn, 203 Fr, 203 Ra) are presented. All available experimental data are compiled and evaluated, and best values for level and γ-ray energies, quantum numbers, lifetimes, γ-ray intensities and transition probabilities, as well as other nuclear properties, are recommended. Inconsistencies and discrepancies that exist in the literature are discussed. A number of computer codes (https://www-nds.iaea.org/public/ensdf_pgm/index.htm) developed by members of the NSDD network were used during the evaluation process. For example, the reported absolute γ-ray emission probabilities and their uncertainties were determined using the GABS code. Here, the γ-ray transition probabilities were determined using the RULER code and the corresponding uncertainties were estimated by means of a Monte-Carlo approach. This work supersedes the earlier evaluation by F.G. Kondev (2005Ko20), published in Nuclear Data Sheets 105, 1 (2005).
Nuclear Data Sheets for A=201
Evaluated nuclear structure and decay data for all nuclei with mass number A=201 ( 201 Os, 201 Ir, 201 Pt, 201 Au, 201 Hg, 201 Tl, 201 Pb, 201 Bi, 201 Po, 201 At, 201 Rn, 201 Fr, 201 Ra) are presented. All available experimental data are compiled and evaluated, and best values for level and γ-ray energies, quantum numbers, lifetimes, γ-ray intensities and transition probabilities, as well as other nuclear properties, are recommended. Inconsistencies and discrepancies that exist in the literature are discussed. A number of computer codes (https://wwwnds.iaea.org/public/ensdf pgm/index.htm) developed by members of the NSDD network were used during the evaluation process. For example, the reported absolute γ-ray emission probabilities and their uncertainties in various decay data sets were determined using the GABS code. The γ-ray transition probabilities were determined using the RULER code and the corresponding uncertainties were determined using a Monte-Carlo approach. In conclusion, this work supersedes the earlier evaluation by F.G. Kondev (2007Ko06), published in Nuclear Data Sheets 108, 365 (2007).
Recommended Nuclear Structure and Decay Data for A = 200 Isobars
Evaluated nuclear structure and decay data for all nuclei with mass number A = 200 ( 200 Os, 200 Ir, 200 Pt, 200 Au, 200 Hg, 200 Tl, 200 Pb, 200 Bi, 200 Po, 200 At, 200 Rn, and 200 Fr), are presented. All available experimental data are compiled and evaluated, and best values for level and gamma-ray energies, quantum numbers, lifetimes, gamma-ray intensities and transition probabilities, as well as other nuclear properties, are recommended. Inconsistencies and discrepancies that exist in the literature are discussed. A number of computer codes (https://www-nds.iaea.org/public/ensdf pgm/) developed by members of the NSDD network were used during the evaluation process. In conclusion, this work supersedes the earlier evaluation by F.G. Kondev and S. Lalkovski (2007Ko42), published in Nuclear Data Sheets 108, 1471 (2007).
Recommended Nuclear Structure and Decay Data for A=206 Isobars
Here, evaluated nuclear structure and decay data for all nuclei with mass number A=206 ( 206 Pt, 206 Au, 206 Hg, 206 Tl, 206 Pb, 206 Bi, 206 Po, 206 At, 206 Rn, 206 Fr, 206 Ra and 206 Ac), are presented. All available experimental data are compiled and evaluated, and best values for level and γ-ray energies, quantum numbers, lifetimes, γ-ray intensities and transition probabilities, as well as other nuclear properties, are recommended. Inconsistencies and discrepancies that exist in the literature are discussed. A number of computer codes (https://www-nds.iaea.org/public/ensdf_pgm/) developed by members of the NSDD network were used during the evaluation process. This work supersedes the earlier evaluation by F.G. Kondev (2008Ko21), published in Nuclear Data Sheets 109, 1527 (2008).
Applying Quantum Tomography to Hadronic Interactions
A proper description of inclusive reactions is expressed with density matrices. Quantum tomography reconstructs density matrices from experimental observables. We review recent work that applies quantum tomography to practical experimental data analysis. Almost all field-theoretic formalism and modeling used in a traditional approach is circumvented with great efficiency. Tomographically-determined density matrices can express information about quantum systems which cannot in principle be expressed with distributions defined by classical probability. Topics such as entanglement and von Neumann entropy can be accessed using the same natural language where they are defined. A deep relation exists between separability, as defined in quantum information science, and factorization, as defined in high energy physics. Factorization acquires a non-perturbative definition when expressed in terms of a conditional form of separability. An example illustrates how to go from data for momentum 4-vectors to a density matrix while bypassing almost all the formalism of the Standard Model.
Is the Kok effect a respiratory phenomenon? Metabolic insight using 13 C labeling in Helianthus annuus leaves
The Kok effect is a well-known phenomenon in which the quantum yield of photosynthesis changes abruptly at low light. This effect has often been interpreted as a shift in leaf respiratory metabolism and thus used widely to measure day respiration. However, there is still no formal evidence that the Kok effect has a respiratory origin. Here, both gas exchange and isotopic labeling were carried out on sunflower leaves, using glucose that was 13 C-enriched at specific C-atom positions. Position-specific decarboxylation measurements and NMR analysis of metabolites were used to trace the fate of C-atoms in metabolism. Decarboxylation rates were significant at low light (including above the Kok break point) and increased with decreasing irradiance below 100 µmol photons m –2 s –1 . The variation in several metabolite pools such as malate, fumarate or citrate, and flux calculations suggest the involvement of several decarboxylating pathways in the Kok effect, including the malic enzyme. Our results show that day respiratory CO 2 evolution plays an important role in the Kok effect. Furthermore, the increase in the apparent quantum yield of photosynthesis below the Kok break point is also probably related to malate metabolism, which participates in maintaining photosynthetic linear electron flow.
Entanglement-Enhanced Neyman-Pearson Target Detection
Quantum illumination (QI) provides entanglement-enabled target-detection enhancement, despite operating in an entanglement-breaking environment. Existing experimental studies of QI have utilized a Bayesian approach, assuming that the target is equally likely to be present or absent before detection, to demonstrate an advantage over classical target detection. However, such a premise breaks down in practical operational scenarios in which the prior probability is unknown, thereby hindering QI's applicability to real-world target-detection scenarios. In this work, we adopt the Neyman-Pearson criterion in lieu of the error probability for equally likely target absence or presence as our figure of merit for QI. We demonstrate an unconditional quantum advantage over the optimal classical-illumination protocol as benchmarked by the receiver operating characteristic, which examines detection probability versus false-alarm probability without resorting to known prior probabilities. Our work represents a critical advancement in adapting quantum-enhanced sensing to practical operational settings.
An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations
We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.
A Practical Approach to Wave Function Propagation, Hopping Probabilities, and Time Steps in Surface Hopping Calculations
We compare several established approaches for propagating wave functions and calculating hopping probabilities within the fewest switches surface hopping (FSSH) algorithm for difficult cases with many electronic states and many trivial crossings. If only a single time step (Δt c ) is employed, we find that no published approach can accurately capture the dynamics correctly unless Δt c → 0 (which is not computationally feasible). If multiple time steps are employed, for a fixed classical time step (Δt c ), a robust scheme can be found for dynamically choosing quantum time steps (δt q1 and δt q2 ) and calculating hopping probabilities so that one can systematically reduce all errors and achieve maximally efficient accuracy; scattering calculations confirm that one can choose a fairly large classical time step. Furthermore, the robust scheme presented here uses both the “local diabatic” and adiabatic interpolation and thus borrows elements from both the Granucci/Persico and Meek/Levine algorithms. Our findings should be broadly applicable in the future.
Beyond the universal Dyson singularity for 1-D chains with hopping disorder
We study a simple non-interacting nearest neighbor tight-binding model in one dimension with disorder, where the hopping terms are chosen randomly. This model exhibits a well-known singularity at the band center both in the density of states and localization length. If the probability distribution of the hopping terms is well-behaved, then the singularities exhibit universal behavior, the functional form of which was first discovered by Freeman Dyson in the context of a chain of classical harmonic oscillators. We show here that this universal form can be violated in a tunable manner if the hopping elements are chosen from a divergent probability distribution. We also demonstrate a connection between a breakdown of universality in this quantum problem and an analogous scenario in the classical domain — that of random walks and diffusion with anomalous exponents.
Lossless Quantum Hard-Drive Memory Using Parity-Time Symmetry
We theoretically studied the feasibility of building a long-term read-write quantum memory using the principle of parity-time (PT) symmetry, which has already been demonstrated for classical systems. The design consisted of a two-resonator system. Although both resonators would feature intrinsic loss, the goal was to apply a driving signal to one of the resonators such that it would become an amplifying subsystem, with a gain rate equal and opposite to the loss rate of the lossy resonator. Consequently, the loss and gain probabilities in the overall system would cancel out, yielding a closed quantum system. Upon performing detailed calculations on the impact of a driving signal on a lossy resonator, our results demonstrated that an amplifying resonator is physically unfeasible, thus forestalling the possibility of PT-symmetric quantum storage. Our finding serves to significantly narrow down future research into designing a viable quantum hard drive.
Path-integral predictions for preasymptotic quantum tunneling
When tunneling occurs out of generic initial states, a significant fraction of probability is lost at early times, during which the dynamics is governed by excited resonance states. However, first-principles analyses based on path-integrals have only captured the leading asymptotic behavior, during which the tunneling rate is dominated by the false vacuum contribution. In this work, we discuss the behavior in the preasymptotic regime from a first-principles path-integral perspective. We demonstrate how the relevant expressions can be evaluated systematically through semiclassical methods in the recently developed steadyon picture. This approach allows one to trace the role of the relevant physical scales, making transparent the underlying assumptions and approximations, and offering a clear path to establishing a systematically improvable framework to evaluate tunneling rates nonperturbatively.
Training a Quantum Annealing Based Restricted Boltzmann Machine on Cybersecurity Data
A restricted Boltzmann machine (RBM) is a generative model that could be used in effectively balancing a cybersecurity dataset because the synthetic data a RBM generates follows the probability distribution of the training data. RBM training can be performed using contrastive divergence (CD) and quantum annealing (QA). QA-based RBM training is fundamentally different from CD and requires samples from a quantum computer. We present a real-world application that uses a quantum computer. Specifically, we train a RBM using QA for cybersecurity applications. The D-Wave 2000Q has been used to implement QA. RBMs are trained on the ISCX data, which is a benchmark dataset for cybersecurity. For comparison, RBMs are also trained using CD. CD is a commonly used method for RBM training. Our analysis of the ISCX data shows that the dataset is imbalanced. We present two different schemes to balance the training dataset before feeding it to a classifier. The first scheme is based on the undersampling of benign instances. The imbalanced training dataset is divided into five sub-datasets that are trained separately. A majority voting is then performed to get the result. Our results show the majority vote increases the classification accuracy up from 90.24% to 95.68%, in the case of CD. For the case of QA, the classification accuracy increases from 74.14% to 80.04%. In the second scheme, a RBM is used to generate synthetic data to balance the training dataset. We show that both QA and CD-trained RBM can be used to generate useful synthetic data. Balanced training data is used to evaluate several classifiers. Among the classifiers investigated, K-Nearest Neighbor (KNN) and Neural Network (NN) perform better than other classifiers. They both show an accuracy of 93%. Our results show a proof-of-concept that a QA-based RBM can be trained on a 64-bit binary dataset. The illustrative example suggests the possibility to migrate many practical classification problems to QA-based techniques. Further, we show that synthetic data generated from a RBM can be used to balance the original dataset.
A practical and efficient approach for Bayesian quantum state estimation
Bayesian inference is a powerful paradigm for quantum state tomography, treating uncertainty in meaningful and informative ways. Yet the numerical challenges associated with sampling from complex probability distributions hampers Bayesian tomography in practical settings. In this article, we introduce an improved, self-contained approach for Bayesian quantum state estimation. Leveraging advances in machine learning and statistics, our formulation relies on highly efficient preconditioned Crank–Nicolson sampling and a pseudo-likelihood. We theoretically analyze the computational cost, and provide explicit examples of inference for both actual and simulated datasets, illustrating improved performance with respect to existing approaches.
Search for charge non-conservation and Pauli exclusion principle violation with the M AJORANA D EMONSTRATOR
Charge conservation and the Pauli exclusion principle result from fundamental symmetries in the standard model of particle physics, and are typically taken as axiomatic. High-precision tests for small violations of these symmetries could point to new physics. Here we consider three models for violation of these processes, which would produce detectable ionization in the high-purity germanium detectors of the M AJORANA D EMONSTRATOR experiment. Using a 37.5 kg yr exposure, we report a lower limit on the electron mean lifetime, improving the previous best limit for the e → v e $\overline{v_e}$ v e decay channel by more than an order of magnitude. Here, we also present searches for two types of violation of the Pauli exclusion principle, setting limits on the probability of an electron to be found in a symmetric quantum state.
Photon-Instanton Collider Implemented by a Superconducting Circuit
Instantons, spacetime-localized quantum field tunneling events, are ubiquitous in correlated condensed matter and high-energy systems. However, their direct observation through collisions with conventional particles has not been considered possible. We show how recent advances in circuit quantum electrodynamics, specifically, the realization of galvanic coupling of a transmon qubit to a high-impedance transmission line, allows the observation of inelastic collisions of single microwave photons with instantons (phase slips). We develop a formalism for calculating the photon-instanton cross section, which should be useful in other quantum field theoretical contexts. In particular, we show that the inelastic scattering probability can significantly exceed the effect of conventional Josephson quartic anharmonicity and reach order-unity values.
Quantum Adiabatic Optimization with Rydberg Arrays: Localization Phenomena and Encoding Strategies
Quantum adiabatic optimization seeks to solve combinatorial problems using quantum dynamics, requiring the Hamiltonian of the system to align with the problem of interest. However, these Hamiltonians are often incompatible with the native constraints of quantum hardware, necessitating encoding strategies to map the original problem into a hardware-conformant form. While the classical overhead associated with such mappings is easily quantifiable and typically polynomial in problem size, it is much harder to quantify their overhead on the quantum algorithm, e.g., the transformation of the adiabatic timescale. In this work, we address this challenge on the concrete example of the encoding scheme proposed in [Nguyen , PRX Quantum , 010316 (2023)], which is designed to map optimization problems on arbitrarily connected graphs into Rydberg atom arrays. We consider the fundamental building blocks underlying this encoding scheme and determine the scaling of the minimum gap with system size along adiabatic protocols. Even when the original problem is trivially solvable, we find that the encoded problem can exhibit an exponentially closing minimum gap. We show that this originates from a quantum coherent effect, which gives rise to an unfavorable localization of the ground-state wave function. On the QuEra Aquila neutral atom machine, we observe such localization and its effect on the success probability of finding the correct solution to the encoded optimization problem. Finally, we propose quantum-aware modifications of the encoding scheme that avoid this quantum bottleneck and lead to an exponential improvement in the adiabatic performance. This highlights the crucial importance of accounting for quantum effects when designing strategies to encode classical problems onto quantum platforms. Published by the American Physical Society 2025