Scattering amplitudes for all masses and spins Arkani-Hamed, Nima; Huang, Tzu-Chen; Huang, Yu-tin
The journal of high energy physics,
11/2021, Letnik:
2021, Številka:
11
Journal Article
Recenzirano
Odprti dostop
A
bstract
We introduce a formalism for describing four-dimensional scattering amplitudes for particles of any mass and spin. This naturally extends the familiar spinor-helicity formalism for massless ...particles to one where these variables carry an extra
SU
(2) little group index for massive particles, with the amplitudes for spin
S
particles transforming as symmetric rank 2
S
tensors. We systematically characterise all possible three particle amplitudes compatible with Poincare symmetry. Unitarity, in the form of consistent factorization, imposes algebraic conditions that can be used to construct all possible four-particle tree amplitudes. This also gives us a convenient basis in which to expand all possible four-particle amplitudes in terms of what can be called “spinning polynomials”. Many general results of quantum field theory follow the analysis of four-particle scattering, ranging from the set of all possible consistent theories for massless particles, to spin-statistics, and the Weinberg-Witten theorem. We also find a transparent understanding for why massive particles of sufficiently high spin cannot be “elementary”. The Higgs and Super-Higgs mechanisms are naturally discovered as an infrared unification of many disparate helicity amplitudes into a smaller number of massive amplitudes, with a simple understanding for why this can’t be extended to Higgsing for gravitons. We illustrate a number of applications of the formalism at one-loop, giving few-line computations of the electron (
g −
2) as well as the beta function and rational terms in QCD. “Off-shell” observables like correlation functions and form-factors can be thought of as scattering amplitudes with external “probe” particles of general mass and spin, so all these objects — amplitudes, form factors and correlators, can be studied from a common on-shell perspective.
The EFT-hedron Arkani-Hamed, Nima; Huang, Tzu-Chen; Huang, Yu-tin
The journal of high energy physics,
05/2021, Letnik:
2021, Številka:
5
Journal Article
Recenzirano
Odprti dostop
A
bstract
We re-examine the constraints imposed by causality and unitarity on the low-energy effective field theory expansion of four-particle scattering amplitudes, exposing a hidden “totally ...positive” structure strikingly similar to the positive geometries associated with grassmannians and amplituhedra. This forces the infinite tower of higher-dimension operators to lie inside a new geometry we call the “EFT-hedron”. We initiate a systematic investigation of the boundary structure of the EFT-hedron, giving infinitely many linear and non-linear inequalities that must be satisfied by the EFT expansion in any theory. We illustrate the EFT-hedron geometry and constraints in a wide variety of examples, including new consistency conditions on the scattering amplitudes of photons and gravitons in the real world.
A
bstract
We construct the defining data of two-dimensional topological field theories (TFTs) enriched by non-invertible symmetries/topological defect lines. Simple formulae for the three-point ...functions and the lasso two-point functions are derived, and crossing symmetry is proven. The key ingredients are open-to-closed maps and a boundary crossing relation, by which we show that a diagonal basis exists in the defect Hilbert spaces. We then introduce regular TFTs, provide their explicit constructions for the Fibonacci, Ising and Haagerup ℋ
3
fusion categories, and match our formulae with previous bootstrap results. We end by explaining how non-regular TFTs are obtained from regular TFTs via generalized gauging.
A three‐dimensional Ni foam deposited with graphene layers on surfaces is used as a conducting solid support to load MoSx catalysts for electrocatalytic hydrogen evolution. The graphene sheets grown ...on Ni foams provide robust protection and efficiently increase the stability in acid. The superior performance of hydrogen evolution is attributed to the relatively high catalyst loading weight as well as its relatively low resistance.
Au–Pd core–shell nanocrystals with tetrahexahedral (THH), cubic, and octahedral shapes and comparable sizes were synthesized. Similar‐sized Au and Pd cubes and octahedra were also prepared. These ...nanocrystals were used for the hydrogen‐evolution reaction (HER) from ammonia borane. Light irradiation can enhance the reaction rate for all the catalysts. In particular, Au–Pd THH exposing {730} facets showed the highest turnover frequency for hydrogen evolution under light with 3‐fold rate enhancement benefiting from lattice strain, modified surface electronic state, and a broader range of light absorption. Finite‐difference time‐domain (FDTD) simulations show a stronger electric field enhancement on Au–Pd core–shell THH than those on other Pd‐containing nanocrystals. Light‐assisted nitro reduction by ammonia borane on Au–Pd THH was also demonstrated. Au–Pd tetrahexahedra supported on activated carbon can act as a superior recyclable plasmonic photocatalyst for hydrogen evolution.
Facets of HER personality: Au–Pd core–shell tetrahexahedral nanocrystals exposing the {730} facet act as efficient plasmonic photocatalyst with the highest turnover frequency value for the hydrogen‐evolution reaction (HER) from ammonia borane under light irradiation.
The axionic weak gravity conjecture predicts the existence of instantons whose actions are less than their charges in appropriate units. We show that the conjecture is satisfied for the ...axion-dilaton-gravity system if we assume duality constraints on the higher derivative corrections in addition to positivity bounds which follow from unitarity, analyticity, and locality of UV scattering amplitudes. On the other hand, the conjecture does not follow if we assume the positivity bounds only. This presents an example where derivation of the weak gravity conjecture requires more detailed UV information than the consistency of scattering amplitudes.
We numerically study an anyon chain based on the Haagerup fusion category and find evidence that it leads in the long-distance limit to a conformal field theory whose central charge is ~2. Fusion ...categories generalize the concept of finite group symmetries to noninvertible symmetry operations, and the Haagerup fusion category is the simplest one which comes from neither finite groups nor affine Lie algebras. As such, ours is the first example of conformal field theories which have truly exotic generalized symmetries. Basically the same result was independently obtained in the preceding Letter Phys. Rev. Lett. 128, 231602 (2022).
This study estimated the prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) according to cardiometabolic risk factors. The long-term impacts of MASLD on all-cause and ...cardiometabolic-specific mortality were evaluated.
We enrolled 343 816 adults aged ≥30 years who participated in a health screening program from 1997 through 2013. MASLD was identified on the basis of abdominal ultrasonography and metabolic profiles. The participants were further categorized by liver enzyme elevation. Baseline cardiometabolic comorbidities were classified on the basis of self-reported medication use and clinical seromarkers. All-cause and cardiometabolic-specific deaths were determined through computerized data linkage with nationwide death certifications until December 31, 2020.
The overall prevalence of MASLD was 36.4%. Among patients with MASLD, 35.9% had abnormal liver enzyme levels. Compared with patients without MASLD, abnormal liver enzymes were positively associated with cardiometabolic comorbidities in patients with MASLD (P
< 0.001). After follow-up, patients with MASLD had a 9%-29% higher risk of all-cause, cardiovascular-related, or diabetes-related mortality. In the groups with MASLD and elevated and normal liver enzyme levels, the multivariate-adjusted hazard ratios for cardiovascular deaths were 1.14 (1.05-1.25) and 1.10 (1.03-1.17), respectively, and those for diabetes deaths were 1.42 (1.05-1.93) and 1.24 (0.98-1.57), respectively, compared with those in the non-MASLD group (P
< 0.001).
Individuals with MASLD and elevated liver enzyme levels exhibited significantly higher risks of all-cause and cardiometabolic deaths and should be monitored and given consultation on cardiometabolic modifications.
Objective
To develop and evaluate the performance of U-Net for fully automated localization and segmentation of cervical tumors in magnetic resonance (MR) images and the robustness of extracting ...apparent diffusion coefficient (ADC) radiomics features.
Methods
This retrospective study involved analysis of MR images from 169 patients with cervical cancer stage IB–IVA captured; among them, diffusion-weighted (DW) images from 144 patients were used for training, and another 25 patients were recruited for testing. A U-Net convolutional network was developed to perform automated tumor segmentation. The manually delineated tumor region was used as the ground truth for comparison. Segmentation performance was assessed for various combinations of input sources for training. ADC radiomics were extracted and assessed using Pearson correlation. The reproducibility of the training was also assessed.
Results
Combining b0, b1000, and ADC images as a triple-channel input exhibited the highest learning efficacy in the training phase and had the highest accuracy in the testing dataset, with a dice coefficient of 0.82, sensitivity 0.89, and a positive predicted value 0.92. The first-order ADC radiomics parameters were significantly correlated between the manually contoured and fully automated segmentation methods (
p
< 0.05). Reproducibility between the first and second training iterations was high for the first-order radiomics parameters (intraclass correlation coefficient = 0.70–0.99).
Conclusion
U-Net-based deep learning can perform accurate localization and segmentation of cervical cancer in DW MR images. First-order radiomics features extracted from whole tumor volume demonstrate the potential robustness for longitudinal monitoring of tumor responses in broad clinical settings.
Summary
U-Net-based deep learning can perform accurate localization and segmentation of cervical cancer in DW MR images.
Key Points
•
U-Net-based deep learning can perform accurate fully automated localization and segmentation of cervical cancer in diffusion-weighted MR images.
•
Combining b0, b1000, and apparent diffusion coefficient (ADC) images exhibited the highest accuracy in fully automated localization.
• First-order radiomics feature extraction from whole tumor volume was robust and could thus potentially be used for longitudinal monitoring of treatment responses.
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