JetFlow: Generating Jets with Conditioned and Mass Constrained Normalising Flows

Fast data generation based on Machine Learning has become a major research topic in particle physics. This is mainly because the Monte Carlo simulation approach is computationally challenging for future colliders, which will have a significantly higher luminosity. The generation of collider data is similar to point cloud generation with complex correlations between the points. In this study, the generation of jets with up to 30 constituents with Normalising Flows using Rational Quadratic Spline coupling layers is investigated. Without conditioning on the jet mass, our Normalising Flows are unable to model all correlations in data correctly, which is evident when comparing the invariant jet mass distributions between ground truth and generated data. Using the invariant mass as a condition for the coupling transformation enhances the performance on all tracked metrics. In addition, we demonstrate how to sample the original mass distribution by interpolating the empirical cumulative distribution function. Similarly, the variable number of constituents is taken care of by introducing an additional condition on the number of constituents in the jet. Furthermore, we study the usefulness of including an additional mass constraint in the loss term. On the \texttt{JetNet} dataset, our model shows state-of-the-art performance combined with fast and stable training

Georg Schmorl prize of the German spine society (DWG) 2022: current treatment for inpatients with osteoporotic thoracolumbar fractures-results of the EOFTT study

AIM Osteoporotic thoracolumbar fractures are of increasing importance. To identify the optimal treatment strategy this multicentre prospective cohort study was performed. PURPOSE Patients suffering from osteoporotic thoracolumbar fractures were included. Excluded were tumour diseases, infections and limb fractures. Age, sex, trauma mechanism, OF classification, OF-score, treatment strategy, pain condition and mobilization were analysed. METHODS A total of 518 patients' aged 75 ± 10 (41-97) years were included in 17 centre. A total of 174 patients were treated conservatively, and 344 were treated surgically, of whom 310 (90%) received minimally invasive treatment. An increase in the OF classification was associated with an increase in both the likelihood of surgery and the surgical invasiveness. RESULTS Five (3%) complications occurred during conservative treatment, and 46 (13%) occurred in the surgically treated patients. 4 surgical site infections and 2 mechanical failures requested revision surgery. At discharge pain improved significantly from a visual analogue scale score of 7.7 (surgical) and 6.0 (conservative) to a score of 4 in both groups (p < 0.001). Over the course of treatment, mobility improved significantly (p = 0.001), with a significantly stronger (p = 0.007) improvement in the surgically treated patients. CONCLUSION Fracture severity according to the OF classification is significantly correlated with higher surgery rates and higher invasiveness of surgery. The most commonly used surgical strategy was minimally invasive short-segmental hybrid stabilization followed by kyphoplasty/vertebroplasty. Despite the worse clinical conditions of the surgically treated patients both conservative and surgical treatment led to an improved pain situation and mobility during the inpatient stay to nearly the same level for both treatments

Treatment and Outcome of Osteoporotic Thoracolumbar Vertebral Fractures With Anterior or Posterior Tension Band Failure (OF 5): Short-Term Results From the Prospective EOFTT Multicenter Study.

STUDY DESIGN Subgroup analysis of a multicenter prospective cohort study. OBJECTIVE To analyse surgical strategies applied to osteoporotic thoracolumbar osteoporotic fracture (OF) 5 injuries with anterior or posterior tension band failure and to assess related complications and clinical outcome. METHODS A multicenter prospective cohort study (EOFTT) was conducted at 17 spine centers including 518 consecutive patients who were treated for an osteoporotic vertebral fracture (OVF). For the present study, only patients with OF 5 fractures were analysed. Outcome parameters were complications, Visual Analogue Scale (VAS), Oswestry Disability Questionnaire (ODI), Timed Up & Go test (TUG), EQ-5D 5L, and Barthel Index. RESULTS In total, 19 patients (78 ± 7 years, 13 female) were analysed. Operative treatment consisted of long-segment posterior instrumentation in 9 cases and short-segment posterior instrumentation in 10 cases. Pedicle screws were augmented in 68 %, augmentation of the fractured vertebra was performed in 42%, and additional anterior reconstruction was done in 21 %. Two patients (11 %) received short-segment posterior instrumentation without either anterior reconstruction or cement-augmentation of the fractured vertebra. No surgical or major complications occurred, but general postoperative complications were observed in 45%. At a follow-up of mean 20 ± 10 weeks (range, 12 to 48 weeks), patients showed significant improvements in all functional outcome parameters. CONCLUSIONS In this analysis of patients with type OF 5 fractures, surgical stabilization was the treatment of choice and lead to significant short-term improvement in terms of functional outcome and quality of life despite a high general complication rate

Treatment and Outcome of Osteoporotic Thoracolumbar Vertebral Body Fractures With Deformation of Both Endplates With or Without Posterior Wall Involvement (OF 4): Short-Term Results from the Prospective EOFTT Multicenter Study.

STUDY DESIGN: Multicenter prospective cohort study. OBJECTIVE: To analyse therapeutical strategies applied to osteoporotic thoracolumbar OF 4 injuries, to assess related complications and clinical outcome. METHODS: A multicenter prospective cohort study (EOFTT) including 518 consecutive patients who were treated for an Osteoporotic vertebral compression fracture (OVCF). For the present study, only patients with OF 4 fractures were analysed. Outcome parameters were complications, Visual Analogue Scale, Oswestry Disability Questionnaire, Timed Up & Go test, EQ-5D 5L, and Barthel Index after a minimum follow-up of 6 weeks. RESULTS: A total of 152 (29%) patients presented with OF 4 fractures with a mean age of 76 years (range 41-97). The most common treatment was short-segment posterior stabilization (51%; hybrid stabilization in 36%). Mean follow up was 208 days (±131 days), mean ODI was 30 ± 21. Dorsoventral stabilized patients were younger compared to the other groups (P .602, Barthel: P > .252, EQ-5D 5L index value: P > .610, VAS-EQ-5D 5L: P = 1.000). The inpatient complication rate was 8% after conservative and 16% after surgical treatment. During follow-up period 14% of conservatively treated patients and 3% of surgical treated patients experienced neurological deficits. CONCLUSIONS: Conservative therapy of OF 4 injuries seems to be viable option in patients with only moderate symptoms. Hybrid stabilization was the dominant treatment strategy leading to promising clinical short-term results. Stand-alone cement augmentation seems to be a valid alternative in selected cases

Clinical Evaluation of the Osteoporotic Fracture Treatment Score (OF-Score): Results of the Evaluation of the Osteoporotic Fracture Classification, Treatment Score and Therapy Recommendations (EOFTT) Study.

STUDY DESIGN Multicenter prospective cohort study. OBJECTIVE The study aims to validate the recently developed OF score for treatment decisions in patients with osteoporotic vertebral compression fractures (OVCF). METHODS This is a prospective multicenter cohort study (EOFTT) in 17 spine centers. All consecutive patients with OVCF were included. The decision for conservative or surgical therapy was made by the treating physician independent of the OF score recommendation. Final decisions were compared to the recommendations given by the OF score. Outcome parameters were complications, Visual Analogue Scale, Oswestry Disability Questionnaire, Timed Up & Go test, EQ-5D 5 L, and Barthel Index. RESULTS In total, 518 patients (75.3% female, age 75 ± 10) years were included. 344 (66%) patients received surgical treatment. 71% of patients were treated following the score recommendations. For an OF score cut-off value of 6.5, the sensitivity and specificity to predict actual treatment were 60% and 68% (AUC .684, P < .001). During hospitalization overall 76 (14.7%) complications occurred. The mean follow-up rate and time were 92% and 5 ± 3.5 months, respectively. While all patients in the study cohort improved in clinical outcome parameters, the effect size was significantly less in the patients not treated in line with the OF score's recommendation. Eight (3%) patients needed revision surgery. CONCLUSIONS Patients treated according to the OF score's recommendations showed favorable short-term clinical results. Noncompliance with the score resulted in more pain and impaired functional outcome and quality of life. The OF score is a reliable and save tool to aid treatment decision in OVCF

JETFLOW: Generating jets with Normalizing Flows using the jet mass as condition and constraint

In this study, jets with up to 30 particles are modelled using Normalizing Flows with Rational Quadratic Spline coupling layers. The invariant mass of the jet is a powerful global feature to control whether the flow-generated data contains the same high-level correlations as the training data. The use of normalizing flows without conditioning shows that they lack the expressive power to do this. Using the mass as a condition for the coupling transformation enhances the model's performance on all tracked metrics. In addition, we demonstrate how to sample the original mass distribution with the use of the empirical cumulative distribution function and westudy the usefulness of including an additional mass constraint in the loss term. On the JetNet dataset, our model shows state-of-the-art performance combined with a general model and stable training

JetFlow: Generating Jets with Conditioned and Mass Constrained Normalising Flows

Fast data generation based on Machine Learning has become a major research topic in particle physics. This is mainly because the Monte Carlo simulation approach is computationally challenging for future colliders, which will have a significantly higher luminosity. The generation of collider data is similar to point cloud generation with complex correlations between the points. In this study, the generation of jets with up to 30 constituents with Normalising Flows using Rational Quadratic Spline coupling layers is investigated. Without conditioning on the jet mass, our Normalising Flows are unable to model all correlations in data correctly, which is evident when comparing the invariant jet mass distributions between ground truth and generated data. Using the invariant mass as a condition for the coupling transformation enhances the performance on all tracked metrics. In addition, we demonstrate how to sample the original mass distribution by interpolating the empirical cumulative distribution function. Similarly, the variable number of constituents is taken care of by introducing an additional condition on the number of constituents in the jet. Furthermore, we study the usefulness of including an additional mass constraint in the loss term. On the \texttt{JetNet} dataset, our model shows state-of-the-art performance combined with fast and stable training

Quantum Angle Generator for Image Generation

The Quantum Angle Generator (QAG) is a new generative model for quantum computers. It consists of a parameterized quantum circuit trained with an objective function. The QAG model utilizes angle encoding for the conversion between the generated quantum data and classical data. Therefore, it requires one qubit per feature or pixel, while the output resolution is adjusted by the number of shots performing the image generation. This approach allows the generation of highly precise images on recent quantum computers. In this paper, the model is optimised for a High Energy Physics (HEP) use case generating simplified one-dimensional images measured by a specific particle detector, a calorimeter. With a reasonable number of shots, the QAG model achieves an elevated level of accuracy. The advantages of the QAG model are lined out - such as simple and stable training, a reasonable amount of qubits, circuit calls, circuit size and computation time compared to other quantum generative models, e.g. quantum GANs (qGANs) and Quantum Circuit Born Machines

Quantum Angle Generator for Image Generation

The Quantum Angle Generator (QAG) is a new generative model for quantum computers. It consists of a parameterized quantum circuit trained with an objective function. The QAG model utilizes angle encoding for the conversion between the generated quantum data and classical data. Therefore, it requires one qubit per feature or pixel, while the output resolution is adjusted by the number of shots performing the image generation. This approach allows the generation of highly precise images on recent quantum computers. In this paper, the model is optimised for a High Energy Physics (HEP) use case generating simplified one-dimensional images measured by a specific particle detector, a calorimeter. With a reasonable number of shots, the QAG model achieves an elevated level of accuracy. The advantages of the QAG model are lined out - such as simple and stable training, a reasonable amount of qubits, circuit calls, circuit size and computation time compared to other quantum generative models, e.g. quantum GANs (qGANs) and Quantum Circuit Born Machines