An innovative path for the detectors at future colliders to achieve higher performances is to use a Particle Flow approach, which requires highly granular calorimeters to image individual showers. The silicon-tungsten electromagnetic calorimeter (SiW-ECAL) aims at fulfilling all the expected physical and technical requirements. SiW-ECAL has been developed by the CALICE and ILD collaborations for more than two decades and is now reaching maturity, for linear machines. However, with the tendency towards circular machines, the progress of electronics and the rapid advancement of machine learning (ML) techniques, the SiW-ECAL design needs to be reoptimised to enhance its performance. This study develops ML-based reconstruction approaches for SiW-ECAL, achieving an approximate 20

The Circular Electron Positron Collider (CEPC) is a large scientific project initiated and hosted by China, fostered through extensive collaboration with international partners. The complex comprises four accelerators: a 30 GeV Linac, a 1.1 GeV Damping Ring, a Booster capable of achieving energies up to 180 GeV, and a Collider operating at varying energy modes (Z, W, H, and ttbar). The Linac and Damping Ring are situated on the surface, while the Booster and Collider are housed in a 100 km circumference underground tunnel, strategically accommodating future expansion with provisions for a Super Proton Proton Collider (SPPC). The CEPC primarily serves as a Higgs factory. In its baseline design with synchrotron radiation (SR) power of 30 MW per beam, it can achieve a luminosity of 5e34 /cm^2/s^1, resulting in an integrated luminosity of 13 /ab for two interaction points over a decade, producing 2.6 million Higgs bosons. Increasing the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons, facilitating precise measurements of Higgs coupling at sub-percent levels, exceeding the precision expected from the HL-LHC by an order of magnitude. This Technical Design Report (TDR) follows the Preliminary Conceptual Design Report (Pre-CDR, 2015) and the Conceptual Design Report (CDR, 2018), comprehensively detailing the machine's layout and performance, physical design and analysis, technical systems design, R&D and prototyping efforts, and associated civil engineering aspects. Additionally, it includes a cost estimate and a preliminary construction timeline, establishing a framework for forthcoming engineering design phase and site selection procedures. Construction is anticipated to begin around 2027-2028, pending government approval, with an estimated duration of 8 years. The commencement of experiments could potentially initiate in the mid-2030s.

The H1 Collaboration reports the first measurement of the 1-jettiness event shape observable $\tau_1^b$ in neutral-current deep-inelastic electron-proton scattering (DIS). The observable $\tau_1^b$ is equivalent to a thrust observable defined in the Breit frame. The data sample was collected at the HERA $ep$ collider in the years 2003-2007 with center-of-mass energy of $\sqrt{s}=319\,\text{GeV}$, corresponding to an integrated luminosity of $351.1\,\text{pb}^{-1}$. Triple differential cross sections are provided as a function of $\tau_1^b$, event virtuality $Q^2$, and inelasticity $y$, in the kinematic region $Q^2>150\,\text{GeV}^{2}$. Single differential cross section are provided as a function of $\tau_1^b$ in a limited kinematic range. Double differential cross sections are measured, in contrast, integrated over $\tau_1^b$ and represent the inclusive neutral-current DIS cross section measured as a function of $Q^2$ and $y$. The data are compared to a variety of predictions and include classical and modern Monte Carlo event generators, predictions in fixed-order perturbative QCD where calculations up to $\mathcal{O}(\alpha_s^3)$ are available for $\tau_1^b$ or inclusive DIS, and resummed predictions at next-to-leading logarithmic accuracy matched to fixed order predictions at $\mathcal{O}(\alpha_s^2)$. These comparisons reveal sensitivity of the 1-jettiness observable to QCD parton shower and resummation effects, as well as the modeling of hadronization and fragmentation. Within their range of validity, the fixed-order predictions provide a good description of the data. Monte Carlo event generators are predictive over the full measured range and hence their underlying models and parameters can be constrained by comparing to the presented data.

A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. The neural network method produced a depth-dependent energy weighting and a time-dependent threshold for enhancing energy deposits consistent with the timescale of evaporation neutrons. Additionally, it was observed to learn an energy-weighting indicative of longitudinal leakage correction. In addition, the method produced a linear detector response and outperformed a published control method regarding resolution for every particle energy studied.

To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to separate energy deposits from charged and neutral particles. Three published neural network-based shower separation models were applied to simulation and experimental data to measure the performance of the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL) technological prototype in distinguishing the energy deposited by a single charged and single neutral hadron for Particle Flow. The performance of models trained using only standard spatial, energy and charged track position information from an event was compared to models trained using timing information available from AHCAL, which is expected to improve sensitivity to shower development and, therefore, aid in clustering. Both simulation and experimental data were used to train and test the models and their performances were compared. The best-performing neural network achieved significantly superior event reconstruction when timing information was utilised in training for the case where the charged hadron had more energy than the neutral one, motivating temporally sensitive calorimeters. All models under test were observed to tend to allocate energy deposited by the more energetic of the two showers to the less energetic one. Similar shower reconstruction performance was observed for a model trained on simulation and applied to data and a model trained and applied to data.

The Breit frame provides a natural frame to analyze lepton–proton scattering events. In this reference frame, the parton model hard interactions between a quark and an exchanged boson defines the coordinate system such that the struck quark is back-scattered along the virtual photon momentum direction. In Quantum Chromodynamics (QCD), higher order perturbative or non-perturbative effects can change this picture drastically. As Bjorken-x decreases below one half, a rather peculiar event signature is predicted with increasing probability, where no radiation is present in one of the two Breit-frame hemispheres and all emissions are to be found in the other hemisphere. At higher orders in α _s or in the presence of soft QCD effects, predictions of the rate of these events are far from trivial, and that motivates measurements with real data. We report on the first observation of the empty current hemisphere events in electron–proton collisions at the HERA collider using data recorded with the H1 detector at a center-of-mass energy of 319 GeV. The fraction of inclusive neutral-current DIS events with an empty hemisphere is found to be 0.0112 ± 3.9%_stat± 4.5%_syst± 1.6%_mod in the selected kinematic region of 150

In high-granularity calorimetry, as proposed for detectors at future Higgs factories, the requirements on electronics can have a strong impact on the design of the detector, especially via the cooling and acquisition systems. This project aims to establish the typical fluxes in the calorimeters: deposited energy, number of cells above the electronics threshold, additional heat, and associated data, etc. Here, a software package is presented which outputs histograms for different selections of the calorimeter components from fully simulated physics and background events. The ILD calorimeter system is taken as a specific example, upon which different histograms are obtained for representative parts of the calorimeter and for various machine configurations. Examples of histograms are shown, along with all details of the data used and the simulation.

AbstractThe H1 Collaboration at HERA reports the first measurement of groomed event shape observables in deep inelastic electron-proton scattering (DIS) at $$\sqrt{s} =319~$$ s = 319 GeV, using data recorded between the years 2003 and 2007 with an integrated luminosity of 351 $$\textrm{pb}^{-1}$$ pb - 1 . Event shapes provide incisive probes of perturbative and non-perturbative QCD. Grooming techniques have been used for jet measurements in hadronic collisions; this paper presents the first application of grooming to DIS data. The analysis is carried out in the Breit frame, utilizing the novel Centauro jet clustering algorithm that is designed for DIS event topologies. Events are required to have squared momentum-transfer $$Q^2 > 150$$ Q 2 > 150 GeV$$^2$$ 2 and inelasticity $$ 0.2< y < 0.7$$ 0.2 < y < 0.7 . We report measurements of the production cross section of groomed event 1-jettiness and groomed invariant mass for several choices of grooming parameter. Monte Carlo model calculations and analytic calculations based on Soft Collinear Effective Theory are compared to the measurements.

We have developed an algorithm dedicated to timing reconstruction in highly granular calorimeters (HGC). The performance of this algorithm is evaluated on an electromagnetic calorimeter (ECAL) with geometries comparable to the electromagnetic compartment (CE-E) of the CMS endcap calorimeter upgrade at HL-LHC and conceptual Particle Flow oriented ECAL’s for future Higgs factories. The time response of individual channel is parameterized according to the CMS experimental result (Akchurin et al. in Nucl Instrum Methods Phys Res Sect A Accel Spectrom Detect Assoc Equip 859:31, 2017). The particle Time-of-Flight (ToF) can be measured with a resolution of 5–20 ps for electromagnetic (EM) showers and 80–160 ps for hadronic showers above 1 GeV. The presented algorithm provides comparable reconstruction with the E_hit^2 weighting strategy and can significantly improve the time resolution compared to a simple averaging of the fast component of the time spectrum. The effects of three detector configurations are also quantified in this study. ToF resolution depends linearly on the timing resolution of a single silicon sensor and improves statistically with increasing incident particle energy. The timing layers at depth of 6–9 radiation lengths provide higher timing performance for EM showers. A clustering algorithm that vetoes isolated hits improves ToF resolution.

An extended version of the CALICE silicon-tungsten ECAL was tested in November 2021 at the DESY beam test facility. With 15 active layers, it featured some with a thin PCB design, and a new compact DAQ system handling all layers in a common set. The noise, self-trigger performances and response to punch-though electrons, without tungsten absorbers, have been evaluated for each of the 15360 channels, using an improved procedure. Showers of low-energy electrons (1 to 6 GeV) have been recorded in two configurations of absorber, and are being analysed. Some preliminary results at the cell level will be presented.

The radiation pattern within high energy quark- and gluon-initiated jets (jet substructure) is used extensively as a precision probe of the strong force as well as an environment for optimizing event generators with numerous applications in high energy particle and nuclear physics. Looking at electron-proton collisions is of particular interest as many of the complications present at hadron colliders are absent. A detailed study of modern jet substructure observables, jet angularities, in electron-proton collisions is presented using data recorded using the H1 detector at HERA. The measurement is unbinned and multi-dimensional, using machine learning to correct for detector effects. All of the available reconstructed object information of the respective jets is interpreted by a graph neural network, achieving superior precision on a selected set of jet angularities. Training these networks was enabled by the use of a large number of GPUs in the Perlmutter supercomputer at Berkeley Lab. The particle jets are reconstructed in the laboratory frame, using the k_T jet clustering algorithm. Results are reported at high transverse momentum transfer Q^2>150 GeV^2, and inelasticity 0.2 < y < 0.7. The analysis is also performed in sub-regions of Q^2, thus probing scale dependencies of the substructure variables. The data are compared with a variety of predictions and point towards possible improvements of such models.

AbstractThe HERAPDF2.0 ensemble of parton distribution functions (PDFs) was introduced in 2015. The final stage is presented, a next-to-next-to-leading-order (NNLO) analysis of the HERA data on inclusive deep inelastic ep scattering together with jet data as published by the H1 and ZEUS collaborations. A perturbative QCD fit, simultaneously of $$\alpha _s(M_Z^2)$$ α s ( M Z 2 ) and the PDFs, was performed with the result $$\alpha _s(M_Z^2)= 0.1156 \pm 0.0011~\mathrm{(exp)}~ ^{+0.0001}_{-0.0002}~ \mathrm{(model}$$ α s ( M Z 2 ) = 0.1156 ± 0.0011 ( exp ) - 0.0002 + 0.0001 ( model $$\mathrm{+ parameterisation)}~ \pm 0.0029~\mathrm{(scale)}$$ + parameterisation ) ± 0.0029 ( scale ) . The PDF sets of HERAPDF2.0Jets NNLO were determined with separate fits using two fixed values of $$\alpha _s(M_Z^2)$$ α s ( M Z 2 ) , $$\alpha _s(M_Z^2)=0.1155$$ α s ( M Z 2 ) = 0.1155 and 0.118, since the latter value was already chosen for the published HERAPDF2.0 NNLO analysis based on HERA inclusive DIS data only. The different sets of PDFs are presented, evaluated and compared. The consistency of the PDFs determined with and without the jet data demonstrates the consistency of HERA inclusive and jet-production cross-section data. The inclusion of the jet data reduced the uncertainty on the gluon PDF. Predictions based on the PDFs of HERAPDF2.0Jets NNLO give an excellent description of the jet-production data used as input.

The International Linear Collider (ILC) is on the table now as a new global energy-frontier accelerator laboratory taking data in the 2030s. The ILC addresses key questions for our current understanding of particle physics. It is based on a proven accelerator technology. Its experiments will challenge the Standard Model of particle physics and will provide a new window to look beyond it. This document brings the story of the ILC up to date, emphasizing its strong physics motivation, its readiness for construction, and the opportunity it presents to the US and the global particle physics community.

The first measurement of lepton-jet momentum imbalance and azimuthal correlation in lepton-proton scattering at high momentum transfer is presented. These data, taken with the H1 detector at HERA, are corrected for detector effects using an unbinned machine learning algorithm (multifold), which considers eight observables simultaneously in this first application. The unfolded cross sections are compared with calculations performed within the context of collinear or transverse-momentum-dependent factorization in quantum chromodynamics as well as Monte Carlo event generators.

In this White Paper for the 2021 Snowmass process, we discuss aspects of precision timing within electromagnetic and hadronic calorimeter systems for high-energy physics collider experiments. Areas of applications include particle identification, event and object reconstruction, and pileup mitigation. Two different system options are considered, namely cell-level timing capabilities covering the full detector volume, and dedicated timing layers integrated in calorimeter systems. A selection of technologies for the different approaches is also discussed.

The strong coupling constant α _s is determined from inclusive jet and dijet cross sections in neutral-current deep-inelastic ep scattering (DIS) measured at HERA by the H1 collaboration using next-to-next-to-leading order (NNLO) QCD predictions. The dependence of the NNLO predictions and of the resulting value of α _s (m_Z) at the Z -boson mass m_Z are studied as a function of the choice of the renormalisation and factorisation scales. Using inclusive jet and dijet data together, the strong coupling constant is determined to be α _s (m_Z) =0.1157 (20)_exp (29)_th . Complementary, α _s (m_Z) is determined together with parton distribution functions of the proton (PDFs) from jet and inclusive DIS data measured by the H1 experiment. The value α _s (m_Z) =0.1142 (28)_tot obtained is consistent with the determination from jet data alone. The impact of the jet data on the PDFs is studied. The running of the strong coupling is tested at different values of the renormalisation scale and the results are found to be in agreement with expectations.

Charged particle multiplicity distributions in positron-proton deep inelastic scattering at a centre-of-mass energy √(s)=319 GeV are measured. The data are collected with the H1 detector at HERA corresponding to an integrated luminosity of 136 pb ^-1 . Charged particle multiplicities are measured as a function of photon virtuality Q^2 , inelasticity y and pseudorapidity η in the laboratory and the hadronic centre-of-mass frames. Predictions from different Monte Carlo models are compared to the data. The first and second moments of the multiplicity distributions are determined and the KNO scaling behaviour is investigated. The multiplicity distributions as a function of Q^2 and the Bjorken variable x_bj are converted to the hadron entropy S_hadron , and predictions from a quantum entanglement model are tested.

The measurement of the jet cross sections by the H1 collaboration had been compared to various predictions including the next-to-next-to-leading order (NNLO) QCD calculations which are corrected in this erratum for an implementation error in one of the components of the NNLO calculations. The jet data and the other predictions remain unchanged. Eight figures, one table and conclusions are adapted accordingly, exhibiting even better agreement between the corrected NNLO predictions and the jet data.

The next generation of collider detectors will make full use of Particle Flow algorithms, requiring high precision tracking and imaging calorimeters. Featuring a granularity by 2 to 3 orders of magnitude higher than existing devices, imaging calorimetry has been developed during the past 15 years by the CALICE collaboration and is now reaching maturity. The state- of-the-art status and the remaining challenges are reviewed here for all investigated sensor types: silicon diode and scintillator for electromagnetic calorimeters, gaseous with semi-digital readout, and scintillator with SiPM readout for hadronic ones. An overview of recent commissioning and beam test results of large-scale technological prototypes and raw performances such as energy resolution, linearity, and studies exploiting the distinct features of granular calorimeters regarding pattern recognition is presented. Beyond these prototypes, the design of experiments addressing the requirements and potential of imaging calorimetry is discussed.