Matthew D. Schwartz
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View article: Precision e+e− hemisphere masses in the dijet region with power corrections
Precision e+e− hemisphere masses in the dijet region with power corrections Open
View article: Diagnostics and new treatment regimens for TB: can the Xpert MTB/XDR assay fill the gap for fluoroquinolone testing?
Diagnostics and new treatment regimens for TB: can the Xpert MTB/XDR assay fill the gap for fluoroquinolone testing? Open
Rapid diagnosis of resistance-conferring mutations to antibiotics used for the treatment of tuberculosis (TB) is critical for patient care and public health control efforts. Prior guidelines included the use of fluoroquinolones (FQs) for t…
View article: Analytic Regression of Feynman Integrals from High-Precision Numerical Sampling
Analytic Regression of Feynman Integrals from High-Precision Numerical Sampling Open
In mathematics or theoretical physics one is often interested in obtaining an exact analytic description of some data which can be produced, in principle, to arbitrary accuracy. For example, one might like to know the exact analytical form…
View article: Applications of the Landau bootstrap
Applications of the Landau bootstrap Open
We advocate a strategy of bootstrapping Feynman integrals from just knowledge of their singular behavior. This approach is complementary to other bootstrap programs, which exploit nonperturbative constraints such as unitarity, or amplitude…
View article: A Precise Determination of $α_s$ from the Heavy Jet Mass Distribution
A Precise Determination of $α_s$ from the Heavy Jet Mass Distribution Open
A global fit for $α_s(m_Z)$ is performed on available $e^+e^-$ data for the heavy jet mass distribution. The state-of-the-art theory prediction includes $\mathcal{O}(α_s^3)$ fixed-order results, N$^3$LL$^\prime$ dijet resummation, N$^2$LL …
View article: Learning the simplicity of scattering amplitudes
Learning the simplicity of scattering amplitudes Open
The simplification and reorganization of complex expressions lies at the core of scientific progress, particularly in theoretical high-energy physics. This work explores the application of machine learning to a particular facet of this cha…
View article: Collective coordinate fix in the path integral
Collective coordinate fix in the path integral Open
Collective coordinates are frequently employed in path integrals to manage divergences caused by fluctuations around saddle points that align with classical symmetries. These coordinates parametrize a manifold of zero modes and more broadl…
View article: Renormalons as Saddle Points
Renormalons as Saddle Points Open
Instantons and renormalons play important roles at the interface between perturbative and non-perturbative quantum field theory. They are both associated with branch points in the Borel transform of asymptotic series, and as such can be de…
View article: The Landau Bootstrap
The Landau Bootstrap Open
We advocate a strategy of bootstrapping Feynman integrals from just knowledge of their singular behavior. This approach is complementary to other bootstrap programs, which exploit non-perturbative constraints such as unitarity, or amplitud…
View article: Reconstructing S-matrix Phases with Machine Learning
Reconstructing S-matrix Phases with Machine Learning Open
A bstract An important element of the S -matrix bootstrap program is the relationship between the modulus of an S -matrix element and its phase. Unitarity relates them by an integral equation. Even in the simplest case of elastic scatterin…
View article: The Collective Coordinate Fix
The Collective Coordinate Fix Open
Collective coordinates are frequently employed in path integrals to manage divergences caused by fluctuations around saddle points that align with classical symmetries. These coordinates parameterize a manifold of zero modes and more broad…
View article: Neural network field theories: non-Gaussianity, actions, and locality
Neural network field theories: non-Gaussianity, actions, and locality Open
Both the path integral measure in field theory (FT) and ensembles of neural networks (NN) describe distributions over functions. When the central limit theorem can be applied in the infinite-width (infinite- N ) limit, the ensemble of netw…
View article: NNLL resummation of Sudakov shoulder logarithms in the heavy jet mass distribution
NNLL resummation of Sudakov shoulder logarithms in the heavy jet mass distribution Open
A bstract The heavy jet mass event shape has large perturbative logarithms near the leading order kinematic threshold at $$ \rho =\frac{1}{3} $$ . Catani and Webber named these logarithms Sudakov shoulders and resummed them at double…
View article: Reconstructing $S$-matrix Phases with Machine Learning
Reconstructing $S$-matrix Phases with Machine Learning Open
An important element of the $S$-matrix bootstrap program is the relationship between the modulus of an $S$-matrix element and its phase. Unitarity relates them by an integral equation. Even in the simplest case of elastic scattering, this …
View article: Constraints on sequential discontinuities from the geometry of on-shell spaces
Constraints on sequential discontinuities from the geometry of on-shell spaces Open
View article: Neural Network Field Theories: Non-Gaussianity, Actions, and Locality
Neural Network Field Theories: Non-Gaussianity, Actions, and Locality Open
Both the path integral measure in field theory and ensembles of neural networks describe distributions over functions. When the central limit theorem can be applied in the infinite-width (infinite-$N$) limit, the ensemble of networks corre…
View article: Sequential discontinuities of Feynman integrals and the monodromy group
Sequential discontinuities of Feynman integrals and the monodromy group Open
We generalize the relation between discontinuities of scattering amplitudes and cut diagrams to cover sequential discontinuities (discontinuities of discontinuities) in arbitrary momentum channels. The new relations are derived using time-…
View article: Reducing the top quark mass uncertainty with jet grooming
Reducing the top quark mass uncertainty with jet grooming Open
The measurement of the top quark mass has large systematic uncertainties coming from the Monte Carlo simulations that are used to match theory and experiment. We explore how much that uncertainty can be reduced by using jet grooming proced…
View article: NNLL Resummation of Sudakov Shoulder Logarithms in the Heavy Jet Mass Distribution
NNLL Resummation of Sudakov Shoulder Logarithms in the Heavy Jet Mass Distribution Open
The heavy jet mass event shape has large perturbative logarithms near the leading order kinematic threshold at $ρ= \frac{1}{3}$. Catani and Webber named these logarithms Sudakov shoulders and resummed them at double-logarithmic level. A re…
View article: Machine learning and LHC event generation
Machine learning and LHC event generation Open
First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide rang…
View article: Prospects for strong coupling measurement at hadron colliders using soft-drop jet mass
Prospects for strong coupling measurement at hadron colliders using soft-drop jet mass Open
A bstract We compute the soft-drop jet-mass distribution from pp collisions to NNLL accuracy while including nonperturbative corrections through a field-theory based formalism. Using these calculations, we assess the theoretical uncertaint…
View article: Finite <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>S</mml:mi></mml:math> matrix
Finite matrix Open
When massless particles are involved, the traditional scattering matrix (S matrix) does not exist: It has no rigorous nonperturbative definition and has infrared divergences in its perturbative expansion. The problem can be traced to the i…
View article: Constraints on Sequential Discontinuities from the Geometry of On-shell Spaces
Constraints on Sequential Discontinuities from the Geometry of On-shell Spaces Open
We present several classes of constraints on the discontinuities of Feynman integrals that go beyond the Steinmann relations. These constraints follow from a geometric formulation of the Landau equations that was advocated by Pham, in whic…
View article: Sudakov shoulder resummation for thrust and heavy jet mass
Sudakov shoulder resummation for thrust and heavy jet mass Open
When the allowed range of an observable grows order-by-order in perturbation\ntheory, its perturbative expansion can have discontinuities (as in the $C$\nparameter) or discontinuities in its derivatives (as in thrust or heavy jet\nmass) ca…
View article: Report on 2203.07460v1
Report on 2203.07460v1 Open
First-principle simulations are at the heart of the high-energy physics research program.They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation.This review illustrates a wide range …
View article: Prospects for strong coupling measurement at hadron colliders using soft-drop jet mass
Prospects for strong coupling measurement at hadron colliders using soft-drop jet mass Open
We compute the soft-drop jet-mass distribution from $pp$ collisions to NNLL accuracy while including nonperturbative corrections through a field-theory based formalism. Using these calculations, we assess the theoretical uncertainties on a…
View article: Simplifying Polylogarithms with Machine Learning
Simplifying Polylogarithms with Machine Learning Open
Polylogrithmic functions, such as the logarithm or dilogarithm, satisfy a number of algebraic identities. For the logarithm, all the identities follow from the product rule. For the dilogarithm and higher-weight classical polylogarithms, t…
View article: Jet charge and machine learning
Jet charge and machine learning Open
Modern machine learning techniques, such as convolutional, recurrent and recursive neural networks, have shown promise for jet substructure at the Large Hadron Collider. For example, they have demonstrated effectiveness at boosted top or <…
View article: Deep learning in color: towards automated quark/gluon jet discrimination
Deep learning in color: towards automated quark/gluon jet discrimination Open
Artificial intelligence offers the potential to automate challenging data-processing tasks in collider physics. Here, to establish its prospects, we explore to what extent deep learning with convolutional neural networks can discriminate q…
View article: Precision direct photon spectra at high energy and comparison to the 8 TeV ATLAS data
Precision direct photon spectra at high energy and comparison to the 8 TeV ATLAS data Open
The direct photon spectrum is computed to the highest currently available precision and compared to ATLAS data from 8 TeV collisions at the LHC. The prediction includes threshold resummation at next-to-next-to-next-to-leading logarithmic o…