ଆକାଡେମିଆ ସିନିକା · ତାଇପେ

ନମସ୍କାର, ମୁଁ ସତ୍ୟଜିତ ପୁହାଣ

ପୋଷ୍ଟଡକ୍ଟୋରାଲ୍ ଗବେଷକ — ହାଡ୍ରନ୍ ଗଠନ ଓ ଲାଇଟ୍-ଫ୍ରଣ୍ଟ QCD

ମୁଁ ପାଇଅନ୍, କାଅନ୍ ଓ ଭାରୀ ମେସନ୍‌ର ଅନ୍ତର୍ନିହିତ ଗଠନ — TMD, GPD ଓ ଫର୍ମ ଫ୍ୟାକ୍ଟର୍ ମାଧ୍ୟମରେ ଅଧ୍ୟୟନ କରେ। NIT ଜାଲନ୍ଧରରେ ୨ ଏପ୍ରିଲ ୨୦୨୬ରେ ପିଏଚ୍‌ଡି ଡିଫେଣ୍ଡ କରିଛି।

44
ପ୍ରକାଶନ
231
ସାଇଟେସନ୍
10
h-index
ବର୍ଷ ଅନୁସାରେ ସାଇଟେସନ୍
  1. 2 2023
  2. 44 2024
  3. 84 2025
  4. 101 2026ଏପର୍ଯ୍ୟନ୍ତ

INSPIRE-HEP ରୁ ଦୈନିକ ସିଙ୍କ୍ · 2026-11-04

ପ୍ରକାଶିତPhys. Rev. D×9PTEP×3Chin. Phys. CEur. Phys. J. AEur. Phys. J. PlusJHEPNucl. Phys. ANucl. Phys. BPhys. Lett. B

Veni, vidi, vici

ଆସିଲି · ଦେଖିଲି · ଜୟ କଲି

ସତ୍ୟଜିତ ପୁହାଣ, ଅଫିସରେ ହ୍ୱାଇଟବୋର୍ଡ ସମ୍ମୁଖରେ
ସହଯୋଗ ପାଇଁ ଉପଲବ୍ଧ

ସଦ୍ୟତମ

ସଦ୍ୟତମ ଖବର ଓ କାର୍ଯ୍ୟକଳାପ

ମୋ ଗବେଷଣା ଯାତ୍ରାର ମୁଖ୍ୟ ମୁହୂର୍ତ୍ତଗୁଡ଼ିକ।

📄 ନୂଆ ଗବେଷଣା ପତ୍ର! 2026-09-30

Diffractive Vector-Meson Production from the Light-Front Quark Model

We study exclusive diffractive electroproduction of the ρ^0, ϕ, J/ψ, and ψ(2S) mesons in the color-dipole picture using two spin-orbit light-front wave functions, S-1 and S-2.

ବିବରଣୀ

📄 ନୂଆ ଗବେଷଣା ପତ୍ର!

Title: Diffractive Vector-Meson Production from the Light-Front Quark Model Authors: S. Puhan Published in: e-Print: 2609.39647 [hep-ph] e-Print: 2609.39647 [hep-ph] INSPIRE-HEP: record 3209881

ସାରାଂଶ

We study exclusive diffractive electroproduction of the ρ^0, ϕ, J/ψ, and ψ(2S) mesons in the color-dipole picture using two spin-orbit light-front wave functions, S-1 and S-2. S-1 follows from the Melosh--Wigner rotation in the light-front quark model (LFQM), while S-2 is the spin-improved form commonly used in holographic and boosted-Gaussian approaches. Both share the same radial wave function, with their parameters determined from the LFQM Hamiltonian. The color-glass-condensate dipole parameters are fixed from inclusive structure-function data, with no fit to diffractive data. We compare the predictions with measurements of cross sections, R=σ_L/σ_T, t and W dependences, and σ_ϕ/σ_ρ. S-1 gives a better description of the light-meson observables, while S-2 provides a better description of the charmonium ratio σ_ψ(2S)/σ_J/ψ and the J/ψ decay constant. We also present the charge, magnetic, and quadrupole form factors of the four mesons and compare them with available lattice-QCD results


INSPIRE-HEP ରୁ ସ୍ୱୟଂଚାଳିତ ଭାବେ ଯୋଡ଼ାଯାଇଛି

📄 ନୂଆ ଗବେଷଣା ପତ୍ର! 2026-09-03

Leading-Neutron Electroproduction at HERA and the EIC: Sullivan Process, Target Fragmentation, and Pion PDFs

Leading-neutron electroproduction measurements from the H1 and ZEUS experiments at HERA have been used to constrain pion parton distribution functions (PDFs) at small momentum…

ବିବରଣୀ

📄 ନୂଆ ଗବେଷଣା ପତ୍ର!

Title: Leading-Neutron Electroproduction at HERA and the EIC: Sullivan Process, Target Fragmentation, and Pion PDFs Authors: W. Chang, C. Hsieh, S. Puhan Published in: e-Print: 2609.03368 [hep-ph] e-Print: 2609.03368 [hep-ph] INSPIRE-HEP: record 3199506

ସାରାଂଶ

Leading-neutron electroproduction measurements from the H1 and ZEUS experiments at HERA have been used to constrain pion parton distribution functions (PDFs) at small momentum fractions within the Sullivan one-pion-exchange (OPE) framework, complementing large-x_π constraints from pion-induced Drell--Yan measurements. Previous analyses have focused primarily on the region of large neutron longitudinal momentum fraction, x_L, where contributions from deep-inelastic scattering (DIS) target fragmentation are suppressed. In this work, we use the Pythia event generator to model the target-fragmentation contribution and show that its combination with the OPE contribution reproduces the main features of the HERA leading-neutron data over the full measured x_L range without introducing additional ad hoc normalization factors. This result demonstrates the potential of incorporating a broader range of leading-neutron data into future global analyses, thereby extending sensitivity to smaller pion momentum fractions x_π. We investigate the model dependence associated with the pion--nucleon vertex form factor and show that the HERA data are sensitive to different target-fragmentation treatments implemented in Pythia. Finally, we present projections for leading-neutron production at the future U.S. Electron-Ion Collider (EIC), identifying beam-energy configurations and kinematic regions that provide enhanced sensitivity to pion structure while suppressing DIS target-fragmentation contributions


INSPIRE-HEP ରୁ ସ୍ୱୟଂଚାଳିତ ଭାବେ ଯୋଡ଼ାଯାଇଛି

📄 ନୂଆ ଗବେଷଣା ପତ୍ର! 2026-08-07

Extraction of Pion Unpolarized Quark and Gluon Generalized Parton Distributions using Deep Neural-Networks

We present a deep neural-network (DNN) extraction of the pion unpolarized quark and gluon generalized parton distributions (GPDs) using the corresponding parton distribution f…

ବିବରଣୀ

📄 ନୂଆ ଗବେଷଣା ପତ୍ର!

Title: Extraction of Pion Unpolarized Quark and Gluon Generalized Parton Distributions using Deep Neural-Networks Authors: S. Puhan, S. Sharma, N. Kumar Published in: e-Print: 2608.07085 [hep-ph] e-Print: 2608.07085 [hep-ph] INSPIRE-HEP: record 3188657

ସାରାଂଶ

We present a deep neural-network (DNN) extraction of the pion unpolarized quark and gluon generalized parton distributions (GPDs) using the corresponding parton distribution functions (PDFs) from the JAM21 and xFitter analysis, together with experimental measurements of the pion electromagnetic form factor (EMFF) and lattice quantum chromodynamics (QCD) results. The GPDs are parameterized using a physics-informed neural-network (PINN) that incorporates the known PDF behavior, an exponential momentum-transfer dependence, and a trainable neural network (NN) component. The network parameters are determined by minimizing a χ^2-based loss function. For the valence-quark GPDs, the loss function includes contributions from the EMFF, squared EMFF, charge-normalization constraints, and regularization terms. For the gluon GPDs, it incorporates constraints from the gluon gravitational form factors together with regularization. This framework enables a flexible, nonparametric extraction while preserving the essential theoretical and phenomenological constraints. By employing the full ensemble of available PDF replicas, we quantify the uncertainties of the extracted GPDs over a broad kinematic range in the longitudinal momentum fraction and momentum transfer, with the uncertainty bands corresponding to the 1σ confidence interval. The extracted valence-quark GPDs are found to be in good agreement with available lattice-QCD calculations. Our study demonstrates that DNN-based methods provide a flexible and robust framework for extracting pion GPDs and probing the multidimensional internal structure of the pion, offering a promising avenue for future investigations of hadron tomography


INSPIRE-HEP ରୁ ସ୍ୱୟଂଚାଳିତ ଭାବେ ଯୋଡ଼ାଯାଇଛି

ସବୁ 21 ଟି ଖବର

Satyajit Puhan

ମୋ ବିଷୟରେ

ଏକ ଛୋଟ ଗାଁରୁ ଆକାଡେମିଆ ସିନିକା

ଓଡ଼ିଶାର ବାଲେଶ୍ୱର ଜିଲ୍ଲାର ଛତ୍ରା ଗାଁରେ ଜନ୍ମ। ପଦାର୍ଥ ବିଜ୍ଞାନରେ JAM-ରେ AIR-877 ଓ JEST-ରେ AIR-209। NIT ଜାଲନ୍ଧରରେ ପିଏଚ୍‌ଡି, ବର୍ତ୍ତମାନ ତାଇପେର ଆକାଡେମିଆ ସିନିକାରେ ପୋଷ୍ଟଡକ୍ଟୋରାଲ ଗବେଷକ।

ପୂରା କାହାଣୀ ପଢ଼ନ୍ତୁ

ଯାତ୍ରାର କିଛି ମୁହୂର୍ତ୍ତ

ସବୁ ଫଟୋ

ମୁଁ କଣ କରେ

ଗବେଷଣା କ୍ଷେତ୍ର

ମୁଁ ଲାଇଟ୍-ଫ୍ରଣ୍ଟ ୱେଭ୍ ଫଙ୍କସନ୍ ଦ୍ୱାରା ପାଇଅନ୍‌ଠାରୁ ବଟମୋନିୟମ୍ ପର୍ଯ୍ୟନ୍ତ ହାଡ୍ରନ୍‌ର ତ୍ରି-ମାତ୍ରିକ, ସ୍ପିନ୍ ଓ ଯାନ୍ତ୍ରିକ ଗଠନ ଅଧ୍ୟୟନ କରେ।

Unpolarized pion TMD f₁(x, k⊥²) in the light-cone quark model
1 / 6

ହାଲୁକା ମେସନ୍‌ର ତ୍ରି-ମାତ୍ରିକ ଚିତ୍ର

ପାଇଅନ୍ ଓ କାଅନ୍‌ର ମୋମେଣ୍ଟମ୍ ଓ ସ୍ଥାନିକ ଟୋମୋଗ୍ରାଫି — TMD, GTMD, GPD ଓ ସ୍ପିନ୍-ଅର୍ବିଟ୍ ସମ୍ପର୍କ।

TMDs to twist-4GTMDsGPDs
Impact-parameter GPD H₁(x, 0, b⊥²) of the J/ψ
2 / 6

ସ୍ପିନ୍-୧ ହାଡ୍ରନ୍ ଓ ଫୋଟନ୍

ρ, J/ψ, Υ ଓ ଫୋଟନ୍‌ର ଗଠନ — TMD, GPD, ଫର୍ମ ଫ୍ୟାକ୍ଟର୍ ଓ PDF।

ρ, J/ψ, ΥTensor polarizationVector GPDs
ηc(2S) light-front wave function, showing its radial node
3 / 6

କ୍ୱାର୍କୋନିୟମ୍ ଓ ଭାରୀ ମେସନ୍

ଚାର୍ମୋନିୟମ୍ ଓ ବଟମୋନିୟମ୍ — ଉତ୍ତେଜିତ ଅବସ୍ଥା, ଡିକେ କନଷ୍ଟାଣ୍ଟ ଓ E1 ବିକିରଣ ପରିବର୍ତ୍ତନ।

CharmoniumBottomoniumRadial excitations
Pressure distribution inside ηc (left) and ηb (right)
4 / 6

ଫର୍ମ ଫ୍ୟାକ୍ଟର୍ ଓ ଯାନ୍ତ୍ରିକ ଗଠନ

ହାଡ୍ରନ୍ ଭିତରେ ଚାପ ଓ ଶିଅର୍ — ଗ୍ରାଭିଟେସନାଲ୍ ଓ ଇଲେକ୍ଟ୍ରୋମ୍ୟାଗ୍ନେଟିକ୍ ଫର୍ମ ଫ୍ୟାକ୍ଟର୍।

Gravitational FFsD-termPressure & shear
Pion light-cone wave function φ(x, k⊥) used as input for the medium study
5 / 6

ନ୍ୟୁକ୍ଲିୟର୍ ପଦାର୍ଥରେ ହାଡ୍ରନ୍

ଘନ ଓ ଉଷ୍ମ ନ୍ୟୁକ୍ଲିୟର୍ ପଦାର୍ଥରେ π, K, ρ, D ଓ B ମେସନ୍‌ର ପରିବର୍ତ୍ତନ।

Chiral SU(3) quark mean fieldIsospin asymmetryFinite temperature
Pion quark density 2πb H^q(x, b) from the neural-network fit, with uncertainty bands
6 / 6

ତଥ୍ୟ-ଭିତ୍ତିକ ନିଷ୍କାସନ ଓ କୋଲାଇଡର୍ ଫେନୋମେନୋଲୋଜି

ନ୍ୟୁରାଲ୍ ନେଟୱାର୍କ ଦ୍ୱାରା ପାଇଅନ୍ GPD ନିଷ୍କାସନ ଓ NICA-SPD, HERA, EIC ପାଇଁ ପୂର୍ବାନୁମାନ।

Neural-network GPDsPion PDFsNICA-SPD

ଗବେଷଣା ବିଷୟରେ ଅଧିକ

ଆଗକୁ

ଭବିଷ୍ୟତ ଗବେଷଣା ଯୋଜନା

ଆଗାମୀ କାର୍ଯ୍ୟ — ଏବେ ଆରମ୍ଭ କରୁଥିବା ସମସ୍ୟାଠାରୁ କଠିନ, ଖୋଲା ପ୍ରଶ୍ନ ପର୍ଯ୍ୟନ୍ତ।

  1. ପରବର୍ତ୍ତୀ ପଦକ୍ଷେପ · ୨୦୨୬–୨୭

    Energy-momentum tensor of spin-1 mesons

    କଠିନତା 3 / 5

    The full set of gravitational form factors of the ρ meson and of heavy vector mesons (J/ψ, Υ) in the light-front quark model — including the D-term — and from them the pressure, shear-force and energy distributions, the mechanical radius and the quadrupole deformation of a spin-1 hadron.

    କାହିଁକି କଠିନ: A spin-1 hadron has six gravitational form factors instead of two, some only reachable from 'bad' current components, and the mechanical picture of a tensor-polarized state is still being worked out.

  2. ମଧ୍ୟମ ଅବଧି · ୨୦୨୭–୨୯

    First-principles light-front quark model for the pion

    କଠିନତା 5 / 5

    Replace the phenomenological Gaussian wave function with the solution of a light-front Hamiltonian eigenvalue problem — confinement, one-gluon exchange and a chiral-symmetry-breaking interaction — with parameters fixed by the meson spectrum, then predict the pion's PDFs, GPDs, TMDs and form factors with no fitting.

    କାହିଁକି କଠିନ: The pion is the Goldstone boson of chiral symmetry: getting a nearly massless bound state from massive constituents on the light front, with zero modes and renormalisation under control, is one of the long-standing open problems of the formalism.

  3. କଠିନ ଖୋଲା ସମସ୍ୟା

    Data-driven 3D tomography with machine learning

    କଠିନତା 4 / 5

    A global extraction of pion GPDs that combines lattice QCD, form-factor and Drell–Yan data with neural networks, with honest uncertainties — building on our deep-neural-network GPD extraction.

    କାହିଁକି କଠିନ: GPDs are not measured directly: the inverse problem from observables to three-dimensional distributions is ill-posed, so the physics constraints (polynomiality, positivity) must be built into the network itself.

ସମ୍ପୂର୍ଣ୍ଣ ଯୋଜନା

My Resume

Academic Background

A journey from a small village in Odisha to the frontiers of High Energy Physics research across India, Japan, Switzerland, and Russia.

ବର୍ତ୍ତମାନ · 2026–Present

Postdoctoral Researcher — Institute of Physics, Academia Sinica

Supervisor: Prof. Wen-Chen Chang. (i) Meson structure via the Sullivan process — extraction of pion and kaon PDFs with phenomenological and neural-net…

2022–2026

Ph.D. in Computational High Energy Physics

Thesis: Tomography of Light and Heavy Mesons Using Light-front Dynamics. Supervisor: Dr. Harleen Dahiya. Successfully defended on 2nd April, 2026. Cou…

Jun–Sep 2025

Visiting Fellow — JINR, Dubna, Russia

Project: Extraction of hadron GPDs using neural networks and energy-momentum tensor calculations. Supervisor: Prof. Oleg V. Teryaev. Joint Institute f…

ପୂରା ବାୟୋଡାଟା

ସହଯୋଗୀ

ସହକର୍ମୀଗଣ |

ଅନୁସନ୍ଧାନକାରୀ ଏବଂ ପରାମର୍ଶଦାତା ମୋର କାମ କରିବାର ସ privilege ଭାଗ୍ୟ ଅଛି |

ହର୍ଲିନ୍ ଡାହିଆ ଡ Associate Professor · Dr. B R Ambedkar NIT, Jalandhar
ପ୍ରଫେସର ଓଲେଗ ଭି ଟେରିଆଭ୍ | Researcher, Joint Institute for Nuclear Research (JINR) · JINR, Dubna
ପ୍ରଫେସର ସାବୟାସୀ ଘୋଷ Collaborator · IIT Bhilai, Chhattisgarh
ପ୍ରଫେସର ଉଜୱାଲ ଲାହା MSc Supervisor · NIT Jamshedpur
ପ୍ରଫେସର ଅରବିନ୍ଦ କୁମାର Collaborator · NIT Jalandhar
ପ୍ରଫେସର ସୁନେଲ ଦତ୍ତ Collaborator · NIT Jalandhar

ସମସ୍ତ 22 ଜଣ ସହଯୋଗୀ

Talks

Talks & News

Presentations at international conferences, seminars, and workshops.

05 April, 2026

PhD Thesis — Acknowledgements

milestone

A heartfelt note of gratitude to everyone who shaped my PhD journey — my mentors, collaborators, friends, and institutions.

ବିବରଣୀ ଦେଖନ୍ତୁ →

ସବୁ ଦେଖନ୍ତୁ

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ମୋ ସହିତ ଯୋଗାଯୋଗ କରନ୍ତୁ

ଗବେଷଣା ସହଯୋଗ, ଆଲୋଚନା କିମ୍ବା ପ୍ରଶ୍ନ ପାଇଁ ଲେଖନ୍ତୁ।

ଠିକଣା Institute of Physics, Academia Sinica, Taipei, Taiwan
ଇମେଲ୍ puhansatyajit@gmail.com
satyajitp.ph.21@nitj.ac.in
ଫୋନ୍ +91-9776342407
କାର୍ଯ୍ୟ ସମୟ Available for research collaborations

ଯୋଗାଯୋଗ ଫର୍ମ

ମୋର ଦାଖଲ ହୋଇଥିବା ଡାଟା ସଂଗ୍ରହ ଓ ସଂରକ୍ଷଣ କରାଯାଉଥିବାରୁ ମୁଁ ସମ୍ମତ ଅଟେ।